Abstract
Animal African Trypanosomiasis (AAT) is a debilitating livestock disease prevalent across sub-Saharan Africa, a main cause of which is the protozoan parasite Trypanosoma congolense. In comparison to the well-studied T. brucei, there is a major paucity of knowledge regarding the biology of T. congolense. Here, we use a combination of omics technologies and novel genetic tools to characterise core metabolism in T. congolense mammalian-infective bloodstream-form parasites, and test whether metabolic differences compared to T. brucei impact upon drug sensitivity. Like T. brucei, glycolysis plays a major part in T. congolense energy metabolism. However, the rate of glucose uptake is significantly reduced in T. congolense, with cells remaining viable when cultured in concentrations as low as 2 mM. Instead of pyruvate, the primary glycolytic endpoints are succinate, malate and acetate. Comparative transcriptomics analysis showed higher levels of activity associated with the mitochondrial pyruvate dehydrogenase complex, acetate generation and the succinate shunt in T. congolense. However, based on omics analysis and chemical inhibition, there does not appear to be significant levels of oxidative phosphorylation. Stable-isotope labelling of glucose enabled the comparison of carbon usage between T. brucei and T. congolense, highlighting differences in nucleotide and fatty acid metabolism. To validate the metabolic similarities and differences, both species were treated with pharmacological inhibitors, confirming a lack of essential electron transport chain activity in T. congolense, but increased sensitivity to inhibition of mitochondrial pyruvate import. Strikingly, T. congolense exhibited significant resistance to inhibitors of fatty acid synthesis, including a 780-fold greater EC50 against the lipase and fatty acid synthase inhibitor Orlistat, compared to T. brucei. These data highlight that bloodstream form T. congolense diverges from T. brucei in key areas of metabolism, with several features that are intermediate between bloodstream- and insect-stage T. brucei. These results have implications for drug development, mechanisms of drug resistance and host-pathogen interactions.
Introduction
The hemoflagellate protozoan parasite Trypanosoma congolense is a primary causative agent of animal African trypanosomiasis (AAT), which can also be caused by T. vivax and T. brucei [1]. AAT accounts for livestock deaths in excess of 3 million annually with up to 120 million cattle at risk [2–4]. Thus, AAT is one of the most important livestock diseases across sub-Saharan Africa.
Current methods of AAT control centre around chemotherapy and prophylaxis (reviewed in [3]), but the very few available veterinary trypanocidal drugs have been used extensively for decades, resulting in resistance and inadequate protection against AAT [5–7]. As such, there is a dire need for the development of new and improved chemotherapeutics to manage AAT [3, 8].
Most of our biological understanding of African trypanosomes derives from studies on T. brucei, subspecies of which, T. b. gambiense and T. b. rhodesiense, cause Human African Trypanosomiasis (HAT) [9]. The ability to culture both procyclic (PCF; tsetse fly) and bloodstream (BSF; mammalian) forms of T. brucei in vitro, combined with its tractability with respect to genetic manipulation, have enabled extensive study of this species on a molecular level [10, 11]. In stark contrast, very few T. congolense strains are amenable to continuous bloodstream form (BSF) culture, with a single strain (IL3000) used in most studies [12]. Whilst genetic modification is possible in T. congolense PCF stage, routine BSF transfection has only recently become possible [13–15]. Additionally, although T. congolense exhibits a superficially similar morphology and life cycle to T. brucei [16, 17] emerging evidence increasingly suggests that T. brucei, T. congolense and T. vivax exhibit some profound differences at the genomic level [18–22], including in genes and phenotypes of direct relevance to infection biology and disease epidemiology. However, there is a lack of understanding to what extent these genetic differences translate into biological differences, including with respect to metabolism.
Understanding metabolism is critical to identifying how pathogens survive and thrive in the varying host environments they encounter, as well as being a means of elucidating drug targets, modes of drug action and mechanisms of drug resistance [23–25]. T. brucei metabolism has been extensively studied, aided by the application of technologies such as liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy (reviewed in detail by [26, 27]), which enable global profiling of the cellular metabolome.
The BSF stage of T. brucei utilizes the high levels of glucose available in the mammalian bloodstream, and depends almost exclusively on the glycolytic pathway to generate ATP [28]. The first seven steps of glycolysis are encompassed by a specialized organelle, the glycosome, which maintains its own ATP/ADP and NAD/NADH balance, allowing glycolysis to proceed at an extraordinarily high rate in comparison to other eukaryotic cells [29]. The endpoint of glycolysis, pyruvate, is a primary waste product of T. brucei, and excreted from the cell in large quantities. As a result, only small amounts of pyruvate are further metabolized in the mitochondrion to acetyl-CoA by pyruvate dehydrogenase (PDH), with acetate the main excretory metabolite in this secondary, yet essential pathway [30]. The acetyl-CoA generated from this pathway is utilized, at least partially, for the de novo synthesis of fatty acids [31]. Indeed, both BSF and PCF T. brucei are highly sensitive to the lipase and fatty acid synthase inhibitor Orlistat [32].
Conversely, in the absence of blood meals, glucose is scarce in the tsetse fly midgut [33], and the main energy source of PCF T. brucei is L-proline, the catabolism of which leads to production of acetate, succinate and L-alanine through a more developed and active mitochondrion (including an active respiratory chain capable of generating ATP, as opposed to the inactive respiratory chain in BSF T. brucei [34]). Until recently, it was thought that PCFT. brucei did not exhibit active TCA metabolism, although recent data have shown that TCA intermediates such as succinate and 2-oxoglutarate can stimulate PCF T. brucei growth. [35–37].
Among the glycolytic enzymes, T. brucei expresses three isoforms of phosphoglycerate kinase, which catalyze the conversion of 1,3-bisphosphoglycerate to 3-phosphoglycerate [38]. These are developmentally regulated, with the major isoform in BSF parasites present in the glycosome (PGK-C), whilst the primary PCF isoform is found in the cytosol (PGK-B) [39]. The localization of PGK-B in the PCF cytosol is thought to result in an ATP/ADP imbalance in the glycosome, which is rectified by upregulating the glycosomal “succinate shunt”, a pathway that includes the ATP-generating phosphoenolpyruvate carboxykinase (PEPCK)- and pyruvate phosphate dikinase (PPDK)-mediated conversion of phosphoenolpyruvate (PEP) to oxaloacetate and pyruvate respectively [39, 40]. The succinate shunt, combined with amino acid metabolism, results in the excretion of high levels of succinate in PCF T. brucei [41].
Stable isotope labelling data has revealed that BSF T. brucei utilize D-glucose to a greater extent than first realized, with heavy carbons disseminating into amino acid, lipid and nucleotide metabolism [42]. This study also showed that some of the succinate and malate excreted from BSF parasites originates from glycolysis and, unexpectedly, inhibition of PEPCK is lethal at this life-cycle stage [42]. It has also been shown that acetate production is essential to BSF T. brucei, in particular for the synthesis of fatty acids (FAs) [30]. However, acetate excretion, as well as that of succinate and malate, is negligible in BSF T. brucei compared to that of pyruvate and L-alanine.
In contrast to T. brucei, the literature on metabolism in T. congolense is scarce. More than half a century ago it was suggested that BSF T. congolense has a significantly lower rate of glucose consumption compared to BSF T. brucei [43]. Furthermore, pyruvate is not the main glycolytic end product and instead, acetate and succinate are excreted at high levels, indicative of metabolism more akin to PCF T. brucei [43]. Further work has revealed additional differences that support this hypothesis [44–46]. For example, BSF T. congolense primarily expresses cytosolic PGK-C, rather than glycosomal PGK-B [46]. Microscopy has also revealed a more developed mitochondrion in BSF T. congolense, with visible cristae, suggesting that mitochondrial energy metabolism could play a more prominent role in BSF T. congolense [47]. The high levels of acetate excretion first shown by Agosin & Von Brand [43] are consistent with this hypothesis. However, other studies have shown that BSF T. congolense is sensitive to inhibitors of Trypanosome Alternative Oxidase (TAO), including salicylhydroxamide (SHAM); and is insensitive to cyanide, suggesting that, as for BSF T. brucei, TAO is the sole terminal oxidase, responsible for reoxidising glycerol 3-phosphate, in BSF T. congolense [48–51]. Notably, nitroblue tetrazolium staining of BSF T. congolense does indicate the presence of NADH dehydrogenase (complex I) activity [48]. However, to date, no studies have assessed BSF T. congolense sensitivity to chemical inhibition of the electron transport chain, or the F1F0-ATPase.
Post-genomic technologies allow for the generation of large datasets that enable analysis of cellular processes on a systems scale, including metabolomics and transcriptomics. Integration of these data can provide a detailed snapshot of cell metabolism at the transcript and metabolite levels and help to dissect differences between species or conditions in unprecedented detail [52]. Furthermore, this knowledge can aid in predication and understanding of drug efficacy and mode of action This study aimed to generate the first comprehensive overview of the metabolome of bloodstream-form T. congolense IL3000 parasites, allowing a global metabolic comparison of differences between T. congolense and T. brucei. Glycolytic metabolism in BSF T. congolense appears to be similar to PCF T. brucei, particularly in terms of metabolic outputs and gene expression. However, there are pronounced differences in parasite reliance on exogenous amino acids as well as carbon dissemination into pathways involved in nucleotide and lipid metabolism, as shown by stable isotope-labelled metabolomics. Using these data, we further validated these metabolic differences in T. congolense by pharmacological inhibition, which highlighted increased sensitivity to inhibition of mitochondrial pyruvate uptake, as well as significant resistance to inhibition of fatty acid synthesis, tested using inhibitors of fatty acid synthase and acetyl-coA synthetase. Taken together, these results suggest that T. congolense and T. brucei differ in some fundamental aspects of their core metabolism, which has important implications in terms drug sensitivity, and therefore, development of novel chemotherapeutics.
Results
Comparative RNA-sequencing of T. congolense and T. brucei
To permit direct comparison of BSF T. congolense and T. brucei at the transcriptome level, RNAseq analysis was carried out on parasites cultured in vitro and trypanosome samples isolated from infected mice at first peak parasitaemia (ex vivo) (Fig 1). Samples were prepared using T. congolense (strain IL3000, in vitro and ex vivo) and pleomorphic T. brucei (strain STIB 247; in vitro and ex vivo), to assess similarities and differences between trypanosomes grown in culture and those from an infection (Fig 1A and 1B), and to compare and contrast the transcriptome across the species (Fig 1C and 1D). Sequencing data were aligned to the respective genome sequence with a mean overall alignment rate of 88.0 ± 2.3% and 94.1 ± 0.7% for T. brucei and T. congolense reads, respectively. Resultant files were sorted and filtered for quality, and to minimize artefacts from multigene families, only uniquely aligned reads were used for downstream analyses. Read counts were normalised using transcripts per million (TPM) [53]. Orthologues were inferred between the species using Orthofinder [54], in order to compare directly TPM values for 1-to-1 orthologues, as well as sum-of-TPM values for groups containing families of paralogues (e.g. hexose transporters). These normalised read counts are henceforth referred to as orthoTPM values (S1 Table). The Orthofinder dataset (S2 Table) consisted of 6,677 orthogroups (denoted with the prefix “TbTc”), of which 5,398 (80.84%) were 1-to-1 orthologues. The Orthofinder tool was also used to predict genes only present in one of the two species (S2 Table). There are several metabolic genes that are not present in the T. congolense genome, including putative delta-4 and delta-6 desaturases (Tb927.10.7100 & Tb11.v5.0580), a succinate dehydrogenase subunit (SDH11; Tb927.8.6890) and guanine deaminase (Tb927.5.4560, Tb05.5K5.200 & Tb11.v5.0409), in addition to mitochondrial pyruvate carrier 1 (MPC1; Tb927.9.3780) (S2 Table).
Differences between four sample groups were assessed based on orthoTPM values (Fig 1; full dataset in S1 Table). There was a strong intra-species correlation between the in vitro and ex vivo conditions at the transcriptome level (T. congolense Pearson correlation coefficient, ρ = 0.765, Fig 1A; T. brucei ρ = 0.803, Fig 1B), showing that in vitro-derived BSF T. congolense and T. brucei closely resemble parasites isolated from infections at the transcriptome level. However, correlations between species even in the same condition were lower, implying transcriptional differences between the species (ex vivo: ρ = 0.651, Fig 1C; in vitro: ρ = 0.687, Fig 1D).
To compare data from this study to BSF T. congolense transcriptomics data generated by Silvester et al. (generated at ascending and peak parasitaemia [55]), TPM values for each annotated T. congolense gene were compared directly (S1 Fig, S3 Table). There was good correlation between both in vitro and ex vivo T. congolense BSF datasets and the data from Silvester et al. (ρ > 0.8, S1 Fig), with the highest correlation being between the ex vivo and ascending data as expected (ρ = 0.897, S1 Fig), albeit the correlation between the ‘ascending’ and ‘peak parasitaemia’ in Silvester et al. was higher (ρ = 0.979, S1 Fig).
T. congolense metabolite consumption and output
Global metabolite (metabolomics) analysis of in vitro culture supernatant samples provides a detailed insight into the metabolic inputs and outputs of cultured cells [56]. However, high levels of medium components can often mask subtle but significant changes in culture medium composition over time. To counteract this, a modified culture medium was designed for T. congolense strain IL3000, based on previous published medium formulations (SCM-3; for details see Materials and Methods) [14, 15].
A time course was initiated in this medium. BSF T. congolense IL3000 cells during exponential growth phase were inoculated into fresh medium (0 h time point). Culture supernatant samples were collected at 0, 8, 24, 32, 48 and 56 hours (n = 4 at each time point) and metabolites extracted for LC-MS analysis.
A total of 290 putative metabolites were detected across all samples (207 after removing putative metabolites that did not map to metabolic pathways, e.g. peptides and medium components), of which 37 were matched to an authentic standard to confidently predict their identity (S4 Table).
80 of the 206 putative metabolites were significantly altered across the dataset (false discovery rate-adjusted P < 0.05; one-way repeated measures ANOVA; Fig 2A and S4 Table). To analyse metabolites undergoing similar changes, K-means clustering with Pearson correlation coefficient as the similarity metric was used, highlighting seven clusters with two clusters of particular interest: one containing metabolites that accumulated over time, and the other containing metabolites depleted over time (Fig. 2A). Log2 fold change (Log2 FC) between the first and final time points (0 and 56 h, respectively) was also calculated for each metabolite (S4 Table).
Glucose, the primary energy source for T. brucei, whilst clearly consumed, was not fully depleted after 56 hours in T. congolense culture (Log2 FC: −0.76; Fig 2A and 3A), in contrast to T. brucei, where 10 mM glucose is consumed by the same time-point [56]. Ribose, glucosamine, inosine and threonine were similarly depleted in T. congolense culture (Log2 FC: −0.78, −0.97, −2.82 and −0.89, respectively).
In contrast, a number of metabolites accumulated in the medium (Fig 2A). The most significant of these were guanine (Log2 FC: 6.34; Fig 2A and 5A), succinate (Log2 FC: 5.60; Fig 2A & 3B) and (S)-malate (malate, Log2 FC: 1.37; Fig 2A and 3B). Interestingly, pyruvate (Log2 FC: 0.24; Fig 3B) was not excreted at the high levels relative to starting concentration consistently observed in BSF T. brucei culture, in both HMI-11 and in Creek’s Minimal medium (CMM) [56]. Succinate and malate appear to be the primary glycolytic outputs from BSF T. congolense, similar to PCF T. brucei. Elevated levels of 2-oxoglutarate and a metabolite putatively identified as 2-oxoglutaramate were observed, which potentially originate from alanine aminotransferase activity using L-glutamate and L-glutamine, respectively, as substrates [42, 57]. Moreover, a significant build-up of N6-Acetyl-L-lysine (Log2 FC: 6.30) was observed (Fig 2B). Whilst the low molecular weight of acetate means it could not be detected by the LC-MS platform used here, concentrations of this molecule were measured directly using an acetate assay in samples taken at the same time points from four independent cultures, which confirmed high levels of acetate excretion by BSF T. congolense (Fig 3F).
Other notable observations included the depletion of several putative lysophosphatidylcholine species at 56 hours (Fig 2A; S4 Table), coincident with increased medium levels of sn-glycero-3-phosphocholine, choline and choline phosphate, indicating lyso-phospholipase activity where the charged headgroup moiety of a lyso-species is cleaved from its bound fatty acid [58]. In addition, tryptophan (Log2 FC: −0.74; Fig 6B; S4 Table) was significantly consumed (P = 0.042), in contrast with cysteine (Log2 FC: −0.07; P > 0.05), despite the latter being essential to T. brucei [59] (S4 Table).
The Log2 metabolite fold changes after 56 hours of culture of T. congolense were compared to those of T. brucei grown in HMI-11 (Fig 2B) [56]. A total of 90 metabolites were identified in both datasets, with some showing divergence between the two species (Fig 2B). Several metabolites only accumulated in T. brucei supernatant, in particular pyruvate, D-glycerate, 2-oxoglutarate and 12-hydroxydodecanoic acid (Fig 2B). Conversely, succinate, N6-acetyl-L-lysine, 4-hydroxy-4-methylglutamate, N6,N6,N6-trimethyl-L-lysine and choline only accumulated in T. congolense supernatant (Fig 2B). Whilst cystine (Fig 2B; 12) was depleted in T. brucei samples, this metabolite remained unchanged in those from T. congolense.
In summary, whilst core elements of metabolism have been conserved between BSF T. congolense and T. brucei, several pronounced differences in T. congolense metabolism were identified based solely on metabolic input and output in in vitro culture. An integrated analysis of the metabolomic and transcriptomic datasets was then undertaken in order to further define the metabolic differences between the two species.
Energy metabolism
As described above, RNA sequencing and culture supernatant metabolomics provided initial indications that T. congolense energy metabolism, specifically with respect to glucose usage, diverges substantially from that characterized in T. brucei BSFs (simplified map of glycolysis depicted in Fig 3G).
To dissect metabolic differences at the transcriptome level, pathway analysis was carried out using the TrypanoCyc database [60], which contains 186 manually curated pathways covering 422 genes or groups of multi-copy genes (S5 Table). These analyses showed broadly similar levels of gene expression of glycolytic components between BSF T. brucei and T. congolense (Fig 3G and 3I). However, the T. brucei ex vivo samples displayed a more distinct expression profile, with low transcript abundances for most glycolytic components compared to all sample groups. This is most likely the result of cells being sampled near peak parasitaemia, and so having a higher proportion of tsetse-transmissible, quiescent short stumpy forms – consistent with this there was elevated expression of stumpy markers such as the PAD array (TbTc_0074), PIP39 (TbTc_0700) and reduced expression of RBP10 (TbTc_0619) (S1 Table) [61–63].
Transcripts associated with gluconeogenesis, the succinate shunt, and the acetate generation pathway were upregulated in BSF T. congolense under both in vitro and ex vivo conditions compared to BSF T. brucei. Key examples of this are pyruvate phosphate dikinase (PPDK), phosphoenolpyruvate carboxykinase (PEPCK), glycosomal malate dehydrogenase (gMDH) and two subunits of pyruvate dehydrogenase (PDH) (Fig 3I). PPDK was previously reported to be expressed in BSF T. congolense, but not BSF T. brucei [44], and it may be assumed that the enzyme serves a similar function in BSF T. congolense as it does in PCF T. brucei; in a mainly glycolytic role to maintain ATP/ADP balance in the glycosome. The high levels of glycosomal MDH expressions in BSF T. congolense contrasts with BSF T. brucei, where gMDH expression is reported to be mostly absent, and cytosolic MDH (cMDH) is the major isoform [64]. The RNAseq analysis also supports a previous study showing high levels of glycerol kinase expression in BSF T. congolense [45]. The most recent PacBio assembly of the T. congolense genome indicates that the parasite encodes five copies of PEPCK in tandem array (TcIL3000.A.H_000300300, TcIL3000.A.H_000300400, TcIL3000.A.H_000300500, TcIL3000.A.H_000300600 & TcIL3000.A.H_000300700; compared to one copy in T. brucei – Tb927.2.4210; [65]), whilst there are only three copies of glycerol kinase in T. congolense (compared to five in T. brucei).
To confirm that the elevated levels of succinate and malate seen in T. congolense spent medium samples originated from glucose, LC-MS analysis using 13C-U-D-glucose was carried out on intracellular metabolites from cell pellet extracts. Stable isotope analysis has provided valuable insights into T. brucei central carbon metabolism [42], and generating T. congolense datasets enabled comparative analysis of glucose catabolism (albeit with an unavoidable difference in medium supplementation of goat serum for T. congolense, rather than foetal bovine serum for T. brucei).
BSF T. congolense was grown for 48 hours in a custom medium (Steketee’s congolense medium; SCM-6; S6 Table), containing a total D-glucose concentration of 10 mM in a 1:1 ratio of D-glucose:13C-U-D-glucose. Following metabolite extraction, LC-MS analysis was undertaken and the majority of glycolytic intermediates were detected, including 13C-labels (Fig 3H). Moreover, labelling ratios of downstream metabolites were largely similar to that of intracellular glucose, and the number of carbons found to be labelled in each metabolite matched that which would be expected in the BSF T. brucei glycolytic pathway (i.e. three 13C atoms in all metabolites downstream of glyceraldehyde 3-phosphate and glycerol-3-phosphate). Similar to T. brucei, a high percentage of 3-carbon labelled fructose-1,6-bisphosphate (FBP) (34.8%) was observed in T. congolense (Fig 3H), probably a result of the “reverse” aldolase reaction occurring in the glycosome [42]. Importantly, two-carbon labelling was observed in several acetylated compounds (N-acetylornithine & N-acetyl-L-lysine; Fig 3H), confirming that acetyl groups used to generate these metabolites originate from D-glucose. Although acetyl-CoA, the product of pyruvate oxidation, was not detected for technical reasons, labelling of acetylated metabolites indicate that glucose-derived pyruvate is used to generate acetyl-CoA and subsequently acetate in the mitochondrion, similar to other trypanosomatids. Taken together, these data indicate that the flow of carbon atoms for glycolytic components in T. congolense is very similar to that in T. brucei. However, the metabolic outputs differ drastically from BSF T. brucei and appear to be more similar to PCF T. brucei.
To determine whether the elevated succinate in supernatants originated from glucose catabolism, metabolite labelling was corrected for the 1:1 (50%) ratio of natural glucose to 13C-U-D-glucose, which equated to a mean percentage labelling of 43.1% (the value is less than 50% due to D-glucose in the serum). All glycolytic metabolites up to pyruvate showed >90% labelling when corrected (for glucose 6-phosphate and fructose-1,6-bisphosphate, both 3-carbon and 6-carbon labels were taken into account), although glycerol and glycerol 3-phosphate exhibited 57.2% and 64.4% labelling, respectively, as these metabolites can also be obtained from catabolism of lipid precursors. Moreover, 40.1% (93.0% corrected) labelling was detected in L-alanine, suggesting that the alanine aminotransferase reaction that utilizes pyruvate to generate 2-oxoglutarate and L-alanine in both BSF and PCF T. brucei, also occurs in BSF T. congolense [42, 66]. For both succinate and malate, 3 carbons are derived from glucose and these metabolites showed 33.6% (78.1% corrected) and 26.0% (60.3% corrected) labelling, respectively. These results suggest that glucose is not the only source of intracellular succinate and malate in T. congolense. However, these values were higher than those reported in T. brucei (70% and 52% for malate and succinate, respectively [42]).
Whilst PCF T. brucei exhibit citric acid (TCA) cycle activity, this pathway is not used to catabolize glucose [35]. Similarly, no citric acid cycle intermediate isotopologues (e.g. citrate) were found when BSF T. congolense were incubated with 13C-U-D-glucose, although small amounts of 2-carbon labelled succinate and malate were observed (Fig 3H). This is similar to BSF T. brucei [42], indicating that, like T. brucei, T. congolense does not appear to couple glycolysis to TCA metabolism and instead directs high amounts of pyruvate through pyruvate dehydrogenase (PDH) into acetyl-CoA and acetate. Taken together, these data suggest that BSF T. congolense both from in vitro cultures and in vivo infection metabolically resemble an intermediate between BSF and PCF T. brucei, with moderate glycolytic capacity and significant levels of succinate shunt activity (glycosomal, rather than mitochondrial; S1 Table) as well as a highly active mitochondrial acetate generating pathway.
Previous work has shown that reduction of glucose concentrations in BSF T. brucei culture from 10 mM to 5 mM leads to decreased cellular motility, reduction in growth and cell body rounding morphology within 8 hours [67]. Given that glucose was not substantially depleted in T. congolense cultures after 56 h, we tested the effect of reduced glucose concentrations on T. congolense viability. Unlike T. brucei, T. congolense was able to maintain a growth rate equal to controls at concentrations as low as 2 mM (Fig 4A) when continuously passaged with no observable change in morphology or motility. To test whether glucose uptake was essential in T. congolense, cells were incubated with D-glucose in addition to varying concentrations of 2-deoxy-D-glucose (2DG), which can be internalised, but not metabolised further than 2-deoxy-D-glucose 6-phosphate, thereby inhibiting glycolysis (Fig 4B). Incubation of T. congolense in medium supplemented with 2DG (in addition to 10 mM glucose) led to growth defects in a dose dependent manner, likely due to 2DG being outcompeted by glucose at lower concentrations (Fig 4B). Although the growth defect was minor in the presence of 1 mM 2DG, there was a more pronounced reduction with 5 mM 2DG. When equimolar concentrations of glucose and 2DG were used, growth was repressed and cell death occurred within 48 hours (Fig 4B). T. congolense viability was also tested in SCM-6 in the presence of N-acetyl-D-glucosamine (GlcNAc), a sugar that inhibits glucose uptake [68] (S2 Fig). In the presence of 60 mM GlcNAc with 10 mM glucose, there was a moderate, yet significant (P < 0.0001 at 96 h, t-test of cell densities) growth defect in T. congolense (S2 Fig). Viability was further reduced when the same concentration GlcNAc was used alongside 2 mM glucose (P < 0.0001 at 96 h, t-test of cell densities), the lowest concentration T. congolense could tolerate (S2 Fig). The rate of glucose consumption was measured by assaying glucose concentrations in cell culture supplemented with 4 mM glucose, and shown to be 47.17 ± 27.91 nmol-1 min-1 108 cells in T. congolense, significantly lower than the rate (132.18 ± 16.31 nmol-1 min-1 108 cells) in T. brucei (n = 4, P = 0.0039; t-test).
To further probe glycolytic metabolism in BSF T. congolense, several targets were selected for RNAi-mediated knock-down, using a tetracycline-inducible T. congolense line expressing T7 polymerase and Tet repressor under puromycin selection (TcoSM [69]). Given that the majority of both malate and succinate appear to originate from glucose catabolism, the effect of reducing expression levels of two proteins involved in the succinate shunt, PEPCK and PPDK (TcIL3000.A.H_000922100 – both expressed at high levels in T. congolense; Fig 3I), was tested in separate experiments (Fig 4C, D). RNAi was induced by addition of 1 µg/mL tetracycline, and cell growth in culture and transcript abundance measured by qPCR were monitored every 24 hours (Fig 4C, D). Creek et al showed that PEPCK is essential in BSF T. brucei, even though the levels of succinate generated through this pathway are negligible [42]. In BSF T. congolense, RNAi targeting the five copies of PEPCK reduced overall PEPCK transcript abundance by approximately 50% (mean transcript levels of 60%, 46% and 63% compared to uninduced controls at 24, 48 and 72 h post-induction, respectively; Fig 4E), leading to a small but non-significant reduction in growth rate (Fig 4C (P=0.0689, t-test at the 96 h time-point). PPDK expression is not detected in BSF T. brucei but is expressed in the PCF stage [44]. Knock-down of PPDK in T. congolense did not affect parasite viability or growth rate (Fig 4D), although similar levels of transcript knockdown were observed (mean transcript levels of 67%, 64% and 50% compared to uninduced controls at 24, 48 and 72 h post-induction, respectively; Fig 4F).
RNAi was also used to knock down expression of the hexose transporter (HT) array, specifically those matching the THT1 and THT2 array in T. brucei (TcIL3000.A.H_000260500, TcIL3000.A.H_000260600, TcIL3000.A.H_000794500, TcIL3000.A.H_000794600, TcIL3000.A.H_000794700.1), which has been shown to significantly restrict growth of BSF T. brucei [70]. Whilst growth rate was unaffected in BSF T. congolense (Fig 4G), induction of HT RNAi led to a reduction in transcript abundance at all time points (mean transcript levels of 83%, 75%, 68% and 65% compared to uninduced controls at 24, 48, 72 and 96 h post-induction, respectively; Fig 4H). Glucose uptake was decreased (mean reduction of 37% in uptake compared to uninduced controls after 72 h; Fig 4I), suggesting that either lower levels of glucose are sufficient for energy generation in T. congolense, or the parasite can utilize other carbon sources for ATP production. These alternatives sources could include serum components such as fatty acids or amino acids, both of which trypanosomatids have been reported to utilise [71, 72].
PCF T. brucei express most components of the electron transport chain (ETC) to generate ATP through oxidative phosphorylation, in contrast to BSF T. brucei, which do not detectably express any ETC components with the exception of the reversed ATPase and alternative oxidase [73]. As mentioned previously, BSF T. congolense is thought to express a complex I NADH dehydrogenase, but it is not known whether BSF T. congolense has capacity for oxidative phosphorylation. Transcriptomics analysis of the ETC was attempted, using a gene list generated by Zikova and colleagues [73], but no significant patterns could be discerned (S1 Table, S3 Fig).
Nucleotide metabolism
Metabolomic analysis of BSF T. congolense culture supernatants indicated a significant uptake of exogenous ribose, a contributor to nucleotide metabolism via uptake, or via the pentose phosphate pathway (PPP; Fig 5A and Fig 2A). Whilst guanosine was not detected in the supernatant, significant accumulation of guanine (Fig 5B) was observed, suggesting either excretion of this metabolite, or, hydrolysis of guanosine through parasite-secreted hydrolases/nucleosidases (previously identified in BSF T. brucei secretomes [74, 75]). This mechanism would enable uptake of guanine and other nucleobases through nucleobase transporters, for which multiple orthologues have been identified in the T. congolense genome [18] through homology with known T. brucei nucleobase transporters TbNT8.1 and TbNBT1 [76, 77]. In addition, there was an accumulation of xanthine, a product of xanthosine hydrolysis, and depletion of inosine, an important nucleoside composed of hypoxanthine and ribose (Fig 5C and 5D). The nucleoside cytidine and the nucleobase hypoxanthine were also detected, but appeared to remain unchanged during the time course, although the latter was a medium supplement potentially added in excess (S4 Table). It is noteworthy that only a single nucleoside transporter gene (TbTc_1072; T. congolense gene IDs: TcIL3000.A.H_000665800 and the pseudogene TcIL3000.A.H_000679300; S2 Table) can be identified in T. congolense, a syntenic homologue of TbNT10 [18], functionally characterized as a P1-type purine nucleoside transporter [78], and is thus unlikely to transport cytidine [79].
Purine salvage is an essential process in trypanosomatids, as they lack the de novo synthesis pathway for the purine ring [80], and previous analysis of cell pellets to investigate intracellular nucleotide metabolism utilizing 13C-U-D-glucose in BSF T. brucei showed purine salvage pathways incorporating 5-carbon labelled ribose derived from glucose [42] (Fig. 5F). Whilst the ribose incorporated into these nucleosides originates almost exclusively from glucose in T. brucei (Fig 5F), T. congolense appears to use far less glucose-derived ribose to make purine nucleosides such as adenosine, guanosine and inosine (Fig 5F).
Transcriptomics analyses indicated upregulation of genes associated with generation of adenosine nucleotides (Fig 5G; red vertical bar), especially in ex vivo T. congolense, as well as hypoxanthine-guanine phosphoribosyltransferase and uracil phosphoribosyltransferase. Upregulation of nucleoside hydrolases and phosphoribosyltransferases supports previous theories based upon genome content that T. congolense has a capacity for nucleobase uptake [18].
The purines guanosine and inosine, which incorporate glucose-derived ribose in T. brucei, were almost entirely unlabelled in T. congolense (Fig 5F). However, the phosphorylated nucleosides GMP, GDP and GTP all incorporate glucose-derived carbon atoms, presumably through ribose. Given the labelling patterns seen in adenosine, one possible explanation could be conversion of AMP to inosine monophosphate (adenosine monophosphate deaminase; TbTc_0145), IMP to xanthosine monophosphate (IMP dehydrogenase; TbTc_1648) and XMP to GMP (GMP synthase; TbTc_1452). However, only one of these enzymes, GMP synthase, was expressed at higher abundance in T. congolense (Log2 fold change: 1.56 and 2.02 for ex vivo and in vitro, respectively). Overall, incorporation of glucose-derived carbons into purine nucleosides is reduced in T. congolense compared to T. brucei. It should be noted that in both experiments, there was no ribose supplementation in the media Of the pyrimidines, uracil and its derivatives were detected during the glucose labelling experiment (S4 Fig). Uracil is known to be the main pyrimidine salvaged by other kinetoplastids including T. brucei [81–83]. Whilst the majority of the uridine, UMP, UDP and UTP pools incorporate glucose-derived ribose (five 13C labels), 5-carbon isotopologues of these pyrimidines were reduced in abundance in T. congolense compared to T. brucei. Instead, 2-carbon labelled isotopologues appeared to comprise the majority of uridine, uracil and their nucleotides (S4 Fig).
Whilst uracil biosynthesis is not essential in T. brucei [84], the uracil pool in T. congolense appears to derive almost entirely from glucose, when corrected for 50% glucose labelling (76% in T. congolense vs 44% in T. brucei [42]; S4 Fig), suggesting that this species predominantly synthesizes uracil from orotate to UMP (orotate phosphoribosyltransferase/orotidine 5-phosphate decarbocylase; TbTc_0735) and from UMP to uracil (uracil phosphoribosyltransferase; TbTc_4220), as can occur in T. brucei [42].
Both these genes are expressed at higher abundance in T. congolense, both in vitro and ex vivo, compared to T. brucei (Fig 5G, S1 Table), which could explain the increased isotopologue labelling. Uridine nucleosides (UMP, UDP, UTP) all show a similar pattern, with significant 2-carbon labelling, as well as moderate levels of 5-carbon labelling from incorporation of glucose-derived ribose (S4 Fig).
These data indicate that, at least under the growth conditions used here, BSF T. congolense favours purine nucleoside salvage in lieu of biosynthesis, in addition to de novo synthesis of orotate, uracil and uridine nucleosides. However, the difference in serum requirements for the two organisms is a confounding factor to the interpretation of this difference.
Amino acid metabolism
It is well established that trypanosomatid parasites scavenge amino acids, key nutrients for survival, from their hosts [85, 86]. Therefore, comparative analyses of T. congolense and T. brucei amino acid metabolism were undertaken. Whilst the majority of amino acids were detected during the supernatant time course, relative abundances in the medium did not vary greatly after 56 hours of in vitro culture (Fig 6A–C, S4 Table). The greatest reductions were observed in threonine (Log2 FC after 56 hours: −0.89; Fig 6A), tryptophan (Log2 FC: − 0.74; Fig 6B), glutamine (Log2 FC: −0.39), asparagine (Log2 FC: −0.35) and phenylalanine (Log2 FC: −0.35). Interestingly, cysteine, an essential factor for the in vitro culture of T. brucei, was not significantly consumed by 56 hours (Log2 FC: −0.07; Fig 6C). However, at least low-level exogenous cysteine is still required to sustain parasite growth in vitro, as viability was significantly affected in the absence of cysteine (for both 1.5 mM and 1 mM vs 0 mM cysteine, P < 0.0001, t-test of cells densities at 96 h; S5 Fig). Experiments were carried out to test the essentiality of all other individual amino acids (with the exception of glutamine, known to be an important amino donor in trypanosomatid metabolism). Using the minimal medium SCM-6, cell viability was monitored for 72 hours in the absence of specific amino acids. Removal of the following amino acids from culture medium led to defects in growth over 72 hours: asparagine, histidine, isoleucine, leucine, methionine, proline, serine, tyrosine and valine (Fig 6D–G). Whilst aspartate appeared to be depleted in spent culture supernatants (S4 Table), this also occurred in the medium only control. Furthermore, removal of aspartate did not lead to reduced cell viability or growth rate in culture (Fig 6F). Long term culture was impossible without the addition of phenylalanine and threonine, leading to a final culture formulation, SCM-7 (S6 Table) containing a total of 14 amino acids. Therefore, BSF T. congolense appears to require a higher number of amino acids than BSF T. brucei, at least in vitro, with CMM containing only 8 amino acids in total, including cysteine and glutamine [56]. To further probe amino acid metabolism, pathway analysis was carried out on the transcriptome (S6 Fig) and metabolome (Fig 6; S6, S7 Fig).
BSF T. brucei utilizes exogenous L-glutamine as the primary source of intracellular glutamate and 2-oxoglutarate and produce significant levels of glutamine-derived succinate [42, 85] (Fig 6I). Given the high levels of succinate excreted by T. congolense, stable isotope labelling was used to determine the contribution of L-glutamine to this pool. T. congolense was incubated for 48 hours with 1 mM 13C-U-L-glutamine and cell pellets analysed by LC-MS. Results indicated the presence of biochemical activities consistent with those observed in T. brucei. Significant glutamine-derived carbon labelling was detected after 48 h incubation for succinate (41.3%, 48.5% corrected), glutamate (76.1%, 89.2% corrected), 2-oxoglutarate (80.5%, 94.3% corrected) and succinate semialdehyde (94.7% corrected; Fig 6I). As would be anticipated, labelling of glutathione (86.1%) and trypanothione (98.4%) from glutamine through glutamate were also observed (S7 Fig). No labelling of malate or aspartate was seen in this study, despite the use of high concentrations of 13C-U-L-glutamine compared to the equivalent study performed in T. brucei with a 50:50 ratio of 13C-U-L-glutamine [85].
The apparent essentiality of several amino acids was also investigated using stable isotope labelling. Proline is an essential carbon source for PCF but not BSF T. brucei [87]. However, removal of proline from BSF T. congolense medium led to reduced growth (Fig 6F). RNAi-mediated knock-down of proline metabolism (specifically pyrroline-5-carboxylate dehydrogenase, TbP5CDH) in PCF T. brucei has highlighted the requirement of proline metabolism for mitochondrial function [87]. Indeed, both P5CDH (TbTc_1695) and proline dehydrogenase (TbTc_1591) expression were upregulated in ex vivo T. congolense, compared to T. brucei, suggesting that proline catabolism was more active (S1 Table and S6 Fig). However, 13C-U-L-proline labelling showed that this amino acid did not contribute to the biosynthesis of other metabolites (S8 Fig). Therefore, the apparent requirement for proline in BSF T. congolense may be for the purposes of polypeptide synthesis only.
As in T. brucei, glucose-derived carbon usage was detected in several amino acids in T. congolense (S6A Fig). Aspartate (a precursor for pyrimidine nucleotide biosynthesis) and alanine (a by-product of a pyruvate-utilising aminotransferase reaction) (S6A Fig) exhibited 3-carbon isotopologues derived from 13C-U-D-glucose. However, in T. brucei, a small proportion of L-asparagine labelling was observed (1.2% 3-carbon labelling) [42], whilst none was observed in T. congolense (S6A Fig). The metabolism of asparagine has not been studied in African trypanosomes; given the reduction of cell growth in the absence of this amino acid (Fig 6F), labelling with 13C-U-L-asparagine was performed, but no other labelled metabolites were detected (S8 Fig). This indicates that, as with proline, protein synthesis is the sole role of asparagine in T. congolense. The reduced expression of asparagine synthetase (TbTc_4894; TcIL3000.A.H_000497800), which converts aspartate to asparagine (S6 Fig), suggests that BSF T. congolense may rely upon scavenging of exogenous asparagine.
Serine was also shown to be essential to T. congolense (Fig 6F), in contrast to minimal culturing requirements for T. brucei [56]. 13C-U-L-serine labelling indicated that T. congolense L-serine metabolism mirrors that of T. brucei in several aspects, such as de novo sphingolipid biosynthesis, with 70.0% 2-carbon labelling of sphinganine and downstream labelling of ceramide and sphingomyelin species (S8 Fig). Similarly, phosphatidylserine decarboxylase activity was evidenced at both transcript and metabolite levels, with 40.1% 2-carbon labelling of glycerol-phospho-ethanolamine (S1 Table; S8 Fig). However, L-serine also has a minor role in S-adenosyl-L-homocysteine detoxification, where serine-derived carbon ultimately contributes to cysteine biosynthesis. In T. congolense, serine-derived carbon labelling can be detected in cystathionine (18.1%) and cysteine (16.7%), through to glutathione (4.1%) and trypanothione disulfide (3-carbon labelled, 6.8%; 6-carbon labelled, 0.02%; S7 Fig). Therefore, the inability to exclude L-serine from T. congolense in vitro culture media may primarily be attributable to lipid metabolism and an increased demand for serine-derived cysteine, potentially over exogenously obtained cysteine, depending on bioavailability. Indeed, metabolomics analysis of culture medium indicates that the ability of T. congolense to take up cysteine from its environment may be lower than in T. brucei (Fig 6C).
Although L-cysteine is primarily a source of sulphur for trypanosomatids, we also investigated the carbon contribution of this amino acid in T. congolense, and in particular, whether L-cysteine-derived carbon atoms contribute to the biosynthesis of glutathione and trypanothione. 13C-U-L-cysteine stable isotope labelling experiments were performed (S7 and S8 Fig). Direct replacement of the 1.5 mM L-cysteine present in SCM with 13C-U-L-cysteine led to high levels of labelling in glutathione and trypanothione disulfide (S7B Fig). This indicates that T. congolense can readily take up and metabolize exogenous cysteine, even though abundance of the amino acid is not reduced significantly over 56 hours of parasite in vitro culture. Although no clear pattern could be observed in transcriptomic analysis of the trypanothione biosynthesis pathway, both trypanothione synthase (TRYS; TbTc_1359) and trypanothione reductase (TRYR; TbTc_4239) were expressed at high levels in in vitro T. congolense cells relative to ex vivo cells, indicating that under in vitro conditions, cells may be subjected to higher levels of oxidative stress (S7C Fig).
Fatty acid metabolism in T. congolense
Lipids have a variety of crucial roles in trypanosomes, as a major constituent of membranes and under certain conditions, for energy [72]. BSF T. brucei require large quantities of myristic acid in particular, for the synthesis of glycosylphosphatidylinositol (GPI) that anchors the parasite’s major surface glycoprotein antigens [88]. To do this, BSF T. brucei both synthesises and scavenges myristic acid. Glucose labelling experiments in T. brucei have shown that myristic acid is partially synthesized from glucose-derived carbon through acetyl-CoA, using a system of fatty acid elongases [89] (Fig 7A). However, no fatty acid carbon labelling was detected after incubation of T. congolense with 13C-U-D-glucose (Fig 7A). Carbon dissemination was also investigated from threonine, which is used as a source of acetate, and thus, lipids [90] (Fig 7B). Similarly, no saturated lipid carbon labelling was observed, suggesting that T. congolense either uses alternative sources of carbon for lipid biosynthesis, or does not rely on acetate as a source of lipids in the same way as T. brucei [30].
While acetate/acetyl-CoA metabolism is highly active at the level of gene expression in T. congolense compared to T. brucei (Fig 7C), consistent with metabolic data, expression of acetyl-CoA synthetase (TbTc_0318), a key enzyme in lipid biosynthesis from acetate, is reduced in both ex vivo and in vitro T. congolense (Fig 7C). Furthermore, an acetyl-CoA thioesterase (TbTc_5515) that is involved in ATP synthesis-uncoupled acetate production in PCF T. brucei [91] is also expressed at lower levels in T. congolense (Fig 7B). Other enzymes involved in fatty acid biosynthesis, namely acetyl-CoA carboxylase (TbTc_0754), −ketoacyl-CoA synthase (TbTc_3372) and β etoacyl-CoA reductase (TbTc_1241), were all expressed at lower abundance in T. congolense than T. brucei, in particular in ex vivo cells (Fig 7C). Of the four elongases, ELO1 (TbTc_0159) and ELO2 (TbTc_1882) were expressed at equal levels in BSF T. congolense, compared to BSF T. brucei (S1 Table). Whilst expression of ELO3 (TbTc_0235) appeared to be reduced in T. congolense (Log2 fold change of −1.98 and −1.62 compared to T. brucei for in vitro and ex vivo, respectively; S1 Table), T. congolense cells expressed higher levels of ELO4 (TbTc_0737) in both in vitro and ex vivo conditions, compared to T. brucei (Log2 fold change: 1.39 and 1.38 for in vitro and ex vivo comparisons, respectively)
The variation in observed gene expression associated with the sterol pathway appeared to correlate with sample condition rather than species (Fig 7C). However, T. congolense transcripts for genes involved in lanosterol synthesis were reduced, especially under in vitro conditions (squalene synthase, SQase, TbTc_2577; squalene monooxygenase, SM, TbTc_3357; lanosterol synthase, LSS, TbTc_4540; Fig 7C).
Fatty acid oxidation was recently confirmed to be an energy source for T. brucei residing in adipose tissue [72]. Transcripts associated with this pathway were less abundant in T. congolense compared to T. brucei under both conditions (Fig 7C), suggesting this may not be an energy-generating pathway in glucose-rich culture medium, or under the in vivo conditions from which they were sampled. However, capacity for ATP generation from fatty acid oxidation should not be ruled out.
Exploiting differences in metabolism for pharmacological intervention
Differences in metabolism between T. congolense and T. brucei have implications for differential drug efficacy between the two species. To validate our findings in key areas of metabolism, pharmacological inhibition was attempted for specific targets in trypanosome metabolism, in order to compare inhibitory concentrations (EC50).
To assess whether areas of mitochondrial metabolism were more essential in BSF T. congolense than in BSF T. brucei, both species were treated with FCCP, an uncoupling agent that depolarises the mitochondrial membrane. However, there was no difference in sensitivity between the species (EC50: 13.0 ± 5.0 µM and 12.6 ± 5.3 µM for T. brucei and T congolense, respectively; Table 1). Given both metabolic and transcriptomic data indicated no increased electron transport chain activity, we also treated with the complex III inhibitor antimycin A, with again no significant differences seen between the species (Table 1). In addition, there was no change in sensitivity to azide, an inhibitor of ATP hydrolysis by the F1-ATPase (Table 1). However, T. congolense appeared to be more resistant to rotenone, a complex I NADH dehydrogenase inhibitor (Table 1). Previous data inferred complex I activity in BSF T. congolense based on nitroblue tetrazolium staining [48]. Rotenone resistance could indicate NADH dehydrogenase activity of a rotenone-insensitive NADH dehydrogenase, such as the inner membrane space-facing NDH2 [92]. T. congolense also showed enhanced sensitivity to salicylhydroxamic acid (SHAM), an inhibitor of the trypanosome alternative oxidase (TAO; Table 1). Taken together, these data indicate that, like T. brucei, T. congolense does not rely on oxidative phosphorylation for ATP production, as indicated by transcriptomics analysis, and that, as previously reported, TAO is the terminal oxidase [48, 51].
Metabolomics and transcriptomics data indicated that T. congolense direct pyruvate towards mitochondrial metabolism, with high transcript levels in PDH and enzymes involved in acetate generation, compared to T. brucei (Fig 3 and 7). We therefore hypothesised T. congolense to be more sensitive to inhibition of mitochondrial pyruvate uptake and to investigate this further, we tested drug sensitivities for UK5099, an inhibitor of mitochondrial pyruvate transport [93]. As expected, T. congolense (EC50: 82.1 µM) was significantly more sensitive (P = 0.0091, unpaired t-test) to UK5099 compared to T. brucei (130.0 µM; Table 1).
Whilst acetate generation appears to be important in T. congolense, our data suggest that the acetate does not appear to be utilised for the biosynthesis of fatty acids, in contrast to what has been shown for T. brucei. To probe this further, we compared drug sensitivity of the two species with compounds targeting fatty acid synthesis (Fig 8). Indeed, T. congolense was significantly more resistant than T. brucei to an acetyl-CoA synthetase inhibitor (ACS inhibitor; 1-(2,3-di(thiophen-2-yl)quinoxalin-6-yl)-3-(2-methoxyethyl)urea, [94]; Fig 8A; Table 1), indicating that acetyl-CoA synthetase is far less essential to this species. ACS is essential to both BSF and PCF T. brucei [30, 95], thus indicating a key metabolic difference between the species.
We next compared drug sensitivity to Orlistat, an inhibitor of fatty acid synthase and phospholipase [32]. Here, a striking difference was found, with T. congolense exhibiting significant resistance (780-fold increase in EC50) to the compound compared to T. brucei (Fig 8B; Table 1), providing further evidence that T. congolense primarily relies on fatty acid scavenging, instead of synthesis, as predicted by the combination of metabolomics and transcriptomics.
Discussion
The protozoan parasite T. congolense is a principal cause of AAT, but crucially, T. brucei remains the dominant model for laboratory-led studies of African trypanosomes, even in the face of mounting evidence that T. brucei and T. congolense differ profoundly in many facets of their biology. In order to facilitate the identification and development of potential drug targets for T. congolense, a detailed understanding of the fundamental cellular metabolism, leading to an understanding of both the differences and commonalities between T. congolense and T. brucei, would be a significant step forward.
Thus, this study aimed to generate a detailed comparison of metabolism in T. congolense and T. brucei, through a combination of metabolomics, transcriptomics and gene knockdown approaches. Transcriptomic data was generated from T. congolense and T. brucei with parasite samples isolated from both in vitro culture and purified from in vivo murine infections (ex vivo). Crucially, there were high levels of correlation between ex vivo and in vitro T. congolense samples, indicating that the cultured form of the parasite closely resembles the in vivo situation, at a transcriptomic level. In contrast, there was lower inter-species correlation between T. brucei and T. congolense.
Our data demonstrate that BSF T. congolense, while possessing some metabolic similarities with BSF T. brucei (as expected), differs substantially in several core components, including in having a reduced reliance on glucose, excretion of distinct glycolytic end products (acetate, malate and succinate in T. congolense compared to pyruvate in T. brucei), and increased gene expression and metabolic signatures of specific mitochondrial pathways, in particular pyruvate to acetate conversion. Additionally, we show increased reliance on exogenous substrates such as ribose for nucleotide synthesis as demonstrated by reduced glucose-derived carbon labelling in nucleoside species in addition to upregulation of hydrolases and phosphoribosyltransferases. Furthermore, while there is overlap in amino acid utilisation (e.g. glutamine), T. congolense relies on more exogenous amino acids than T. brucei. Surprisingly, this included serine which, in the case of T. congolense, appears to be important in the transsulfuration pathway that is geared towards trypanothione biosynthesis. This may also explain the observed decreased reliance on exogenous L-cysteine. Unlike T. brucei, T. congolense also requires asparagine and proline for viable in vitro culture, although carbon usage from these amino acids is minimal. Finally, T. congolense exhibits increased acetate/acetyl-CoA metabolism compared to T. brucei, despite a reduction in fatty acid biosynthesis through the classical trypanosomatid pathways-ketoacyl-CoA synthase and β ketoacyl-CoA reductase, the expression of which are reduced in T. congolense (both in ex vivo and in vitro conditions). This is further underlined by lack of glucose-derived 2-carbon labelling of fatty acids, most notably myristic acid, a key GPI anchor component of variant surface glycoproteins of T. brucei. However, fatty acid elongase 4, previously shown to extend exogenously scavenged arachidonic acid (C22:4) to docosatetraenoic acid (C22:4) [96], is upregulated under in vitro conditions, compared to T. brucei, which may indicate a reliance on long-chain polyunsaturated fatty acids. These findings are shown in a summary figure of in vitro transcriptomics data (Fig 9)
Analyses of culture supernatants showed that 10 mM glucose was not substantially depleted after T. congolense cultures reached high cell density, as would be expected from an equivalently dense T. brucei culture [56]. T. brucei requires at least 5 mM glucose in culture [67], whereas BSF T. congolense were viable and maintained doubling times in levels as low as 2 mM. Furthermore, confirming conclusions from one previous study on BSF T. congolense [43], the primary metabolic outputs in vitro were (S)-malate, succinate and acetate, in contrast to T. brucei, in which the main output is pyruvate, which is excreted in large amounts [42, 56]. Interestingly, we observed a reproducible reduction in pyruvate levels in T. congolense supernatants over time, before abundance of this metabolite returned to levels similar to those observed in negative controls. A recent study in PCF T. brucei demonstrated that these parasites can re-metabolize glycolytic end products such as pyruvate and succinate [37]. Stable isotope labelling patterns in catabolic products derived from glucose do not support cyclical TCA activity, nor re-uptake of excreted metabolites in BSF T. congolense. However, it would be of interest to determine whether this species can recycle the aforementioned metabolites.
T. congolense exhibits high levels of expression in genes involved in the glycosomal succinate shunt (PEPCK, glycosomal malate dehydrogenase and fumarate hydratase; Fig 9). In T. brucei these phenotypes are associated with PCF rather than BSF; thus, to further dissect glycolytic metabolism, RNAi was employed to investigate the essentiality of PPDK and PEPCK in T. congolense. In T. brucei, PPDK is only expressed in the PCF stage, and is absent in the BSF stage. In contrast, BSF T. congolense expresses PPDK at both transcript (Fig 3) and protein [44] levels, although our initial analyses suggest that the protein is not essential for growth in vitro. PEPCK was previously found to be essential in BSF T. brucei [42]; though in BSF T. congolense, PEPCK knock-down only led to a mild reduction in growth rate. Previous studies in PCF T. brucei demonstrated that individual null mutants of PEPCK and PPDK showed no change in growth rate, with moderate reductions in glycolytic flux [40]. However, a PEPCK/PPDK null mutant did exhibit reduced growth rates, with further data showing that PPDK functions in a glycolytic direction and contributes to glycosomal ATP/ADP balance [40]. Further work is required to establish the roles of PEPCK and PPDK in BSF T. congolense. Gene knock-out has not been previously attempted for T. congolense, and consistent with other studies RNAi penetrance does not appear as efficient as in T. brucei [69]. Techniques such as CRISPR/Cas9 and conditional knock-out would greatly enhance our capabilities to study this parasite.
Whilst the major PGK isoform in BSF T. brucei is expressed in the glycosome, a previous study suggested that the major isoform of phosphoglycerate kinase in BSF T. congolense lacks the glycosomal targeting signal present in T. brucei, and is thus expressed in the cytosol, akin to PCF T. brucei [46]. This has significant implications for glycosomal ADP/ATP balance, as the expression of cytosolic PGK in BSF T. brucei is lethal [39]. Taken together, these data suggest that T. congolense appears to carry out glycolytic metabolism in the same fashion as PCF, not BSF T. brucei, including in ex vivo cells.
Whilst 2-deoxy-D-glucose does cause T. congolense death in vitro and supplementation of cultures with GlcNAc also has a detrimental impact on viability, knock-down of the glucose transporter array did not affect growth, even though glucose uptake appeared to be reduced by 37% subsequent to 72 h of RNAi induction. These experiments highlight a crucial difference between BSF T. congolense and T. brucei in a pathway that has become a metabolic paradigm in the latter species. Whilst T. brucei requires high levels of glucose to sustain a significant glycolytic flux, T. congolense remains viable in significantly lower glucose concentrations, with a reduced flux, more similar to PCF T. brucei. However, glucose remains an essential carbon source in this species, as growth is abolished in the absence of glucose. Of particular interest is whether the parasite generates the majority of ATP from this reduced glucose intake, or if it can thrive on other carbon sources such as amino acids or even fatty acids. If the latter, this adaptation could be due to the reduced bioavailability of glucose in the ruminant host bloodstream. Blood concentrations of glucose in humans are approximately 5.5 mM [97]. Glucose concentrations in ruminants are typically lower (2–4 mM [98–100]), and primary sources of energy are typically volatile fatty acids in the form of acetic, propionic and butyric acid [101, 102]. To date, products of volatile fatty acid metabolism, such as 2-methylcitrate and 2-methyl-cis-aconitase, have not been reported in T. congolense. As such, the ability of T. congolense to utilise other products only available in adult ruminant blood merits further investigation.
RNAseq analyses of T. congolense indicate high levels of expression of mitochondrial pathways associated with glucose catabolism, specifically acetate and acetyl-CoA metabolism involving pyruvate dehydrogenase, acetate:succinate CoA transferase and succinyl-CoA synthetase (Fig 9). Given that the large amounts of acetate generated by the parasite appear not to be required for fatty acid synthesis, these findings could suggest significant reliance on mitochondrial substrate level phosphorylation for growth, similar to PCF T. brucei cultured in glucose-rich medium [103, 104]. Interestingly, T. congolense does not appear to encode a homologue of MPC1, and therefore likely relies on MPC2 for pyruvate transport into the mitochondrion. The lack of multiple pyruvate transporters combined with the importance of mitochondrial pyruvate catabolism likely explains the increased sensitivity of T. congolense to UK5099, a mitochondrial pyruvate transport inhibitor, compared to T. brucei.
Our data are consistent with the absence of oxidative phosphorylation, based on transcriptomics and lack of sensitivity to chemical inhibition, compared to T. brucei. Interestingly, a previous study reported NADH dehydrogenase (complex I) activity in T. congolense, offering the possibility of ATP generation via complex V [48]. However, there was no change in rotenone sensitivity in T. congolense, suggesting that the NADH dehydrogenase activity may originate from a rotenone-insensitive NADH dehydrogenase such as NDH2, known to be important for acetate production in BSF T. brucei [92, 105, 106].
Rather than oxidative phosphorylation, we propose it is likelier that considerable ATP production occurs in the acetate:succinate CoA transferase – succinyl-CoA synthetase (SCS) cycle, which would explain the high levels of acetate generated by T. congolense, in addition to increased sensitivity to inhibition of mitochondrial uptake of pyruvate, the key metabolic precursor. Given that 2-oxoglutarate dehydrogenase complex expression appears to be less than, or equal to, that in T. brucei (under in vitro culturing conditions, Fig 9), it is likely that SCS activity occurs in the acetate-generating pathway rather than in the TCA cycle, which is not thought to be fully functional in BSF African trypanosomes [35], although recent data have challenged this paradigm in PCF T. brucei [37]. The mechanisms proposed here bear some similarities to the scheme proposed by Dewar and colleagues for stumpy-form T. brucei metabolism, which also exhibit increased mitochondrial metabolism compared to BSF T. brucei [107].
In T. brucei, carbon atoms from glucose disseminate through multiple pathways in the cell [42] and, using stable isotope-labelled glucose, our data demonstrate that this pattern is also seen in T. congolense, in particular through the glycolytic pathway, suggesting some of the key metabolic differences observed are quantitative, rather than qualitative. However, there were key differences in glucose-derived carbon usage. In particular, a reduction in labelling was observed in purine nucleotides in T. congolense. In both species, carbon labelling is likely due to generation of ribose phosphate sugars via the PPP and these data suggest that T. congolense does not obtain its ribose through the pentose phosphate pathway (from glucose), to the same extent that T. brucei does. Interestingly, T. congolense appears to express higher levels of APRT1 (cytosolic) compared to APRT2 (glycosomal) to synthesise adenosine (Fig 5). This discrepancy could underpin the reduced fraction of glucose-derived purine labelling, with a reliance on ribose from alternative sources (for example, exogenously).
Whilst the majority of pyrimidine labelling is 5-carbons in T. brucei, indicating labelled ribose, there is decreased 5-carbon labelling and higher abundance of 2-carbon labelling in T. congolense, likely through uridine generated from aspartate through orotate, again highlighting a reduction in glucose-derived ribose, but conversely, an increase in glucose-derived UMP and its derivatives.
There was also a reduced abundance of glucose-derived fatty acid labelling in T. congolense relative to T. brucei. Coupled with a decreased abundance of acetyl-CoA synthetase mRNA, these results suggest that T. congolense may scavenge exogenous lipids in favour of carrying out fatty acid biosynthesis, for which it must break down extracellular lipids to their constituent parts. Indeed, supernatant metabolomics showed accumulation of both choline and choline phosphate, with a corresponding decrease in the LysoPC lipids, which appears to indicate activity of the phospholipases which T. congolense is known to secrete [58, 108]. It is unknown whether T. congolense is able to generate cytosolic acetyl-CoA for fatty acid biosynthesis through the action of citrate lyase, although transcript abundance of this gene was reduced compared to T. brucei. Analysis of drug sensitivity supports these conclusions, as T. congolense is significantly less sensitive to acetyl-CoA synthetase inhibition, as well as Orlistat, and inhibitor of fatty acid synthase, suggesting that fatty acid scavenging (e.g. lipid or fatty acid transporters) could be a viable therapeutic target for this species.
BSF T. brucei growth in CMM required only cysteine and glutamine when supplemented with FBS gold, although a further 6 amino acids (Tyr, Phe, Trp, Leu, Met and Arg) were required when supplemented with standard FBS [56]. As part of this study, 14 amino acids essential for T. congolense growth were identified. Tryptophan and arginine, essential to T. brucei, were not required to sustain T. congolense growth in 10% goat serum. Conversely, several amino acids considered not essential to T. brucei were crucial for T. congolense growth in vitro (Asp, His, Ile, Pro, Ser and Val). Proline is a well-established carbon source for PCF T. brucei [87]. However, based on stable isotope labelling experiments, this amino acid is solely used for protein synthesis in BSF T. congolense, as there was no evidence of carbon dissemination from proline into the metabolome (likewise for asparagine). Unlike BSF T. congolense, BSF T. brucei must be able to synthesise sufficient amounts of these amino acids from alternative sources, or obtain them from the serum supplement.
One metabolic area of interest in trypanosomatids is trypanothione biosynthesis, a crucial pathway for parasite response to oxidative stress. Indeed, trypanothione synthase, as well as proteins involved in the trypanothione biosynthesis pathway, such as ornithine decarboxylase (targeted by Eflornithine), have long been considered prime chemotherapeutic targets due to their absence from other organisms [109]. Whilst cysteine was previously known to be a main carbon contributor to trypanothione synthesis in T. brucei along with glutamine and methionine [85], we show here that L-serine, an amino acid essential to T. congolense, also contributes to the generation of this metabolite. Interestingly, L-cysteine was not significantly depleted from T. congolense culture supernatants and future work should ascertain whether the presence of L-serine in medium can compensate for reduced L-cysteine levels in T. congolense culture.
The data presented here have led to the generation of a novel semi-defined medium for culturing the strain IL3000, which must be further optimized for the culture of multiple strains of T. congolense. Of interest is the peculiar requirement of adult bovine or goat serum for in vitro culture of T. congolense, rather than foetal bovine serum (FBS) which is typically used to culture T. brucei [15, 59]. Whilst this study made no attempts to adapt T. congolense to FBS-supplemented medium (indeed, even in SCM-7, growth rate is drastically reduced in the presence of FBS after 2-3 passages), this is of crucial importance, as it would allow the study of multiple species of African trypanosome under the same in vitro conditions. Analysis of metabolism presented here indicates that this phenomenon is likely to centre on the lipid requirements of T. congolense, although it remains to be seen if this requirement is for energy generation or synthesis of lipids in general. Furthermore, adult ruminant serum composition drastically differs from that of non-ruminants and of foetal ruminants [101, 102], and this likely has significant implications on the extracellular environment faced by livestock trypanosomes.
The information presented here is a significant step in laying the foundation for fundamental understanding of metabolism for an important livestock parasite. Understanding essential areas of metabolism in both T. brucei and T. congolense enables the development of drugs effectively targeting both species. Conversely, understanding the key differences between the two species aids in dissecting drug mechanisms of action and resistance, as well as enabling a greater understanding of host-pathogen dynamics.
Materials and Methods
Compounds and reagents
All compounds were obtained from Sigma/Merck with the exception of: Orlistat (Cambridge Bioscience), oligomycin A (VWR International), diminazene aceturate (Cambridge BioScience) and FCCP (Abcam).
Cell lines and in vitro culture
In all cases, T. congolense strain IL3000 [48] was used (originally received from Theo Baltz, University of Bordeaux). For RNAi experiments a T. congolense IL3000 single marker line, TcoSM, was used [69]. For in vitro experiments, cells were grown at 34°C, 5% CO2 and routinely cultured in either TcBSF3 [14] or HMI-93 [15], in both cases without a serum plus supplement, with 20% goat serum (Gibco). For global metabolite analysis of culture supernatant, an experimental medium (SCM-3) was used with the following components: 77 mM NaCl, 1.5 mM CaCl2, 4.5 mM KCl, 0.8 mM MgSO4, 36 mM NaHCO3, 25 mM HEPES, 0.05 mM bathocuproinedisulfonic acid, 0.22 mM 2-mercaptoethanol, 50 U/mL penicillin/streptomycin, 2.5 mM glucose, 1 mM pyruvate, 10 % goat serum, 10% TcBSF3 [14], 1 mM each of L-cysteine and L-glutamine, and 100 µM L-tyrosine, L-phenylalanine, L-tryptophan, L-leucine, L-methionine and L-arginine. BSF T. congolense in exponential growth phase were centrifuged at 1,500 × g for 10 minutes, washed with PBS and inoculated into this medium (0 h time point).
For stable isotope labelling experiments, as well as experiments involving the removal or addition of specific medium components, a custom medium, Steketee’s Congolense Medium-6 (SCM-6) was used (S6 Table). The final medium formulation based on this study’s findings, SCM-7, is provided in S6 Table. This medium is essentially HMI-93, although i) vitamins (with the exception of folate) were removed, ii) D-glucose concentrations were modified depending on experimental procedure, but was routinely kept at 10 mM, iii) goat serum levels were reduced to 10% and, iv) of the 20 amino acids, 14 were added. Increasing the temperature to 37°C led to a detrimental effect on cell viability after several passages, as previously reported [15].
For experiments involving T. brucei, either the monomorphic Lister 427 (in vitro experiments and growth curves) or pleomorphic STIB 247 (RNAseq experiments, both in vitro and ex vivo sample groups) strains were used. Lister 427 cells were grown in HMI-11 [110], whilst STIB 247 were grown in modified HMI-9 containing 1.1% methylcellulose and 20% serum plus (Sigma) [111, 112]. In both cases, cells were incubated at 37°C, 5% CO2.
For both species, cell counts were carried out using a haemocytometer, and in the case of T. congolense, cells were mechanically detached from the culturing plasticware by pipetting prior to counting. Growth curves were routinely carried out in 2 mL samples incubated in 24-well plates, resuspended using a P1000. For detachment of cells from flasks, 10 mL plastic pipettes were used. In cases where cells were harvested for experiments other than those involving metabolomics, cells could also be detached by replacing the medium with PBS for incubating at room temperature for several minutes, prior to vigorously tapping the flask to detach parasites.
RNAi experiments using TcoSM were carried out in HMI-93 in 20 mL cultures. Cells were seeded at 7 × 105 cells/mL and RNAi induction was initiated with the addition of 1 µg/mL tetracycline (Sigma) and 1 × 107 cells were isolated every 24 hours for RNA analysis (outlined below) before cells were passaged
Ethics statement
All animal experiments were performed in accordance with the Animals (Scientific Procedures) Act 1986 and the University of Glasgow care and maintenance guidelines. All animal protocols and procedures were approved by The Home Office of the UK government and the University of Glasgow Ethics Committee.
Animal experiments
Adult female CD-1 mice (20–30 g body weight; Charles River Laboratories) were infected with 5 × 104 wild-type T. brucei STIB 247 or 1 × 105 wild-type T. congolense IL3000 by intraperitoneal injection. Parasitaemia was monitored daily by venesection of the lateral tail vein [113]. At first peak of parasitaemia (>107 cells/mL) mice were euthanised and blood isolated. Parasites of both species were purified from blood by anion exchange using DEAE cellulose [114]. Purified cells were counted, and a total of 1 × 108 cells were centrifuged for 10 minutes at 1,500 × g prior to RNA extraction.
RNA extraction
For RNAseq experiments, 108 cells were isolated either from in vitro culture or from mouse infections. RNA was extracted using the QIAgen RNeasy kit (Qiagen) with an on-column DNase treatment step. Sample concentrations were analysed by Nanodrop and QuBit, and concentrations adjusted to 37 ng/µL of which 80 µL (2.96 µg) was submitted for RNAseq.
For RNAi time course experiments, cell pellets (107 cells) were resuspended in 1 mL TRIzol (Invitrogen) and stored at −80°C. Samples were thawed, 200 µL chloroform was added, samples were shaken vigorously for 15 seconds and incubated at room temperature for 3 minutes, prior to centrifugation at 12,000 × g for 15 minutes, 4°C. The aqueous layer was transferred to a fresh tube and 500 µL isopropanol and 1 µL Glycoblue (Invitrogen) were added. Samples were mixed by inverting, incubated at room temperature for 10 minutes and centrifuged at 12,000 × g for 10 minutes at 4°C. RNA pellet was washed in ice-cold 75% ethanol and centrifuged at 12,000 × g for 10 minutes at 4°C. After air-drying, RNA was resuspended in 20 µL RNase-free water and concentration adjusted to 100 ng/µL. DNase treatment was carried out using the Ambion TURBO DNase kit (Applied Biosystems) as per manufacturer’s instructions.
Metabolomics sample preparation
For metabolomics analysis of supernatants, 10 mL T. congolense cultures were incubated in T25 flasks in relevant media. Cells were centrifuged at 1,500 × g for 10 minutes, washed with PBS, resuspended in relevant media and density adjusted to 1 × 105 cells/mL. At each time-point, 500 µL medium was transferred to a 1.5 mL eppendorf tube and briefly quenched in a dry ice/ethanol bath, before centrifuging at 1,500 × g for 10 minutes at 4°C. A 5 µL aliquot was then transferred to a new eppendorf containing 200 µL metabolite extraction solvent (chloroform:methanol:water in a 1:3:1 ratio) and samples vortexed at 4°C for one hour. Samples were centrifuged for 5 minutes at 13,000 × g (4°C) and supernatants transferred to new eppendorfs. Samples were stored at −80°C prior to analysis.
For analysis of intracellular metabolites, cells were grown to a final density of 2 × 106 cells/mL and a total of 108 cells isolated. Cells were quenched in 50 mL falcon tubes to 4°C using a dry ice/ethanol bath (stirred and measured by thermometer) and all subsequent steps were carried out at 4°C. Cells were centrifuged at 1,500 × g for 10 minutes and if supernatant samples were required in addition to cell pellets, 5 µL was transferred to an eppendorf containing 200 µL extraction solvent. Cells were resuspended in residual medium before transfer to eppendorf tubes. Cells were then centrifuged (1,500 × g, 5 minutes) and washed twice with ice-cold phosphate buffered saline (PBS) before resuspension in 200 µL extraction solvent (chloroform:methanol:water in a 1:3:1 ratio). Samples were vortexed at 4°C for 1 hour, and then centrifuged for 5 minutes at 13,000 × g. Supernatants were transferred to clean eppendorf tubes. For all experiments, a quality control sample was generated by pooling 10 µL from each sample and samples were stored under argon gas at −80°C.
Primers and plasmids
RNAi experiments were carried out using a T. congolense single marker line, TcoSM [69] that expresses Tet repressor and T7 polymerase, maintained in 0.5 µg/mL puromycin, and gene specific RNAi constructs were introduced with a T. congolense specific plasmid, p3T7-TcoV [69]. Primers carrying a HindIII (5’-AAGCTT-forward) or an FseI (5’-GGCCGGCC-reverse) restriction site were used to amplify TcoPEPCK, TcoPPDK and TcoHT (S7 Table). Gene fragments were amplified using a HiFi polymerase master mix (NEB) and cloned into pGEM-T easy (Promega) and sequenced to confirm correct sequence identity of each fragment. The constructs were then digested with HindIII and FseI and ligated into the p3T7-TcoV vector using T4 DNA ligase (Promega). The final plasmid was linearised with NotI before purification by ethanol precipitation prior to electroporation into TcoSM cells.
Transfections/electroporations
T. congolense IL3000 electroporation experiments and selection experiments were performed as developed by [69]. A total of 4 × 107 cells were used per transfection, including a negative (buffer only) control. A transfection buffer previously published for use with T. brucei was used for T. congolense transfections [115]. Cells were centrifuged at 1,500 × g for 10 minutes, pellets resuspended in residual medium and transferred to eppendorf tubes for a further centrifugation step. Cells were subsequently washed in transfection buffer prior to final resuspension in 100 µL buffer per transfection. Up to 12 µg linearised plasmid DNA was added to an electroporation cuvette (Sigma), and 100 µL cells were subsequently added. Electroporation was carried out using a Nucleofector II (Lonza) programme Z-001. Transfected cells were then incubated overnight in 25 mL warm medium in the absence of selective antibiotics, prior to their addition and plating out at dilutions of 1:50, 1:100 and 1:200 in 96-well plates. Antibiotics were added at the following concentrations: Puromycin: 0.5 µg/mL; Neomycin (G418): 0.4 µg/mL. Clones were retrieved after 7-10 days, and these were maintained in 0.25 µg/mL puromycin and 0.2 µg/mL G418.
Drug sensitivity assays
Drug sensitivity assays were carried out using the alamar blue method developed by Raz and colleagues [116]. Briefly, Compounds were diluted to 2× starting concentration in SCM-6 (with 10% goat serum for T. congolense IL3000 or 10% FBS for T. brucei Lister 427) and 200 µL was transferred to the first well of a solid white flat-bottomed 96-well plate. 100 µL medium was then added to 23 further wells and compounds were diluted 1:2 over this series of wells, with the exception of the last well, for a negative control. Subsequently, 100 µL cells were added at 2× starting density (4 × 104 cells/mL for T. brucei and 5 × 105 cells/mL for T. congolense). Plates were incubated for 48 hours (37°C or 34°c for T. brucei and T. congolense, respectively, 5% CO2 in both cases), prior to addition of 20 µL resazurin sodium salt (0.49 mM in 1× PBS, pH 7.4) to each well. Plates were then incubated for a further 24 hours before measurements of cell viability.
Reduction of the resazurin salt was measured as a function of cell viability. Fluorescence of each plate was read using a Cytation 5 imaging reader (BioTek) and GEN5 software. Parameters were as follows: λexcitation = 540 nm and λemission = 590 nm. Raw values were plotted against concentrations (converted to Log10 values) and normalised (0% defined as smallest mean in the dataset; 100% defined as largest mean in the dataset) using Graphpad Prism version 8.4.0. EC50 values for each compound were calculated using a non-linear sigmoidal dose-response curve. Each assay was performed in duplicate and each EC50 value represents a mean of three independent experiments.
Real-time quantitative PCR (RT-qPCR)
RNA was extracted as described above, and reverse transcription was carried out in 20 µL using 1 µg RNA, using a high capacity cDNA kit (Applied Biosystems). Primers for RT-qPCR analysis were designed using Primer 3 [117], and primer efficiency was tested using serial dilutions of T. congolense IL3000 genomic DNA by plotting Ct value against Log10(DNA concentration). Real-time PCR was carried out using the SensiFAST SYBR Hi-ROX kit (Bioline, BIO92005). Briefly, a 20 µL reaction was set up using 10 µL SYBR mix, RT template and 400 nM of each primer. Cycling conditions were: 96°C, 120 seconds, followed by 40 cycles of 95°C for 5 seconds, 62°C for 10 seconds and 72°C for 20 seconds. Previously published endogenous control primers for TcoTERT were used for within sample normalisation [118], and normalised transcript level was calculated using the delta delta Ct method [119].
Glucose uptake assays
For analysis of wild-type T. congolense and T. brucei glucose uptake, cells were seeded in 10 mL cultures of SCM-6 at an initial density of 2 × 105 cells/mL (four cultures per species), with 10 mM glucose added separately at the start of the experiment. Upon the addition of glucose, 1 mL supernatant was immediately centrifuged (1,500 × g, 10 minutes) and supernatant stored at −80°C. This process was repeated at 12, 15, 18, 21 and 24 h, and cell density measured by haemocytometer. A medium-only control (4 replicates) was also incubated alongside in vitro cultures. Glucose concentration of each supernatant sample was analysed using the Glucose (GO) assay kit (GAGO-20; Sigma) in a 96-well format. Briefly, 40 µL supernatant sample (diluted if necessary) was incubated with 80 µL assay reagent for 30 minutes at 37°C, after which 80 µL 12 N sulphuric acid was added and absorbance measured at 540 nm using a spectrophotometer. A standard curve was also run to calculate glucose concentration. Rate of glucose consumption was calculated using a custom script [57].
For glucose consumption of the TcoHT RNAi line, the Glucose Uptake-Glo kit (Promega) was used. RNAi was induced for 72 hours prior to carrying out the assay. Cells were centrifuged, washed in PBS and resuspended in assay buffer (77 mM NaCl, 1.5 mM CaCl2-2H2O, 4.5 mM KCl, 0.8 mM MgSO4-7H2O, 36 mM NaHCO3, 25 mM HEPES and 0.02 mM bathocuproinedisulfonic acid), as it was determined T. congolense viability is reduced in PBS alone. Density was adjusted to 108 cells/mL, and three 100 µL replicates of each sample were added to wells of a black flat-bottomed 96-well plate. The uptake reaction was started by the addition of 50 µL 1 mM 2-deoxy-D-glucose. Plate was shaken for 15 minutes at 34°C prior to addition of 25 µL stop buffer, 25 µL neutralisation buffer and 100 µL pre-prepared 2DG6P detection reagent. Plates were shaken in between addition of the buffers. Finally, the plate was read with 0.3–1 second integration on a luminometer (Cytation 5 Imaging reader, BioTek). Wild-type T. congolense, and T. congolense supplemented with glucose were used as controls, in addition to cells without 2-deoxy-D-glucose and assays in the absence of cells.
Metabolomics – Liquid chromatography mass spectrometry
Hydrophilic interaction liquid chromatography (HILIC) was carried out by Glasgow Polyomics (Glasgow, UK), using a Dionex UltiMate 3000 RSLC system (Thermo Fischer Scientific) coupled to a ZIC-pHILIC column (150 mm × 4.6 mm, 5 µm column, Merch Sequant). The column was maintained at 30°C and samples were eluted with a linear gradient (20 mM ammonium carbonate in water and acetonitrile) over 26 minutes with a flow rate of 0.3 mL/minute.
Sample injection volume was 10 µL and samples were maintained at 4°C before injection. A Thermo Orbitrap Exactive (Thermo Fischer Scientific) was used to generate mass spectra, and was operated in polarity switching mode with the following settings: Resolution: 50,000; AGC: 106; m/z range: 70–1,400; sheath gas: 40; auxiliary gas: 5; sweep gas: 1; probe temperature: 150°C; capillary temperature: 275°C. Samples were run in both positive and negative polarity with the following ionisation: source voltage +4.5 kV, capillary voltage +50 V, tube voltage +70 kV and skimmer voltage +20 V for positive mode; source voltage −3.5 kV, capillary voltage −50 V, tube voltage −70 V and skimmer voltage −20 V for negative mode.
Mass calibration was performed for each polarity immediately prior to each analysis batch. The calibration mass range was extended to cover small metabolites by inclusion of low-mass contaminants with the standard Thermo calmix masses (below m/z 1400), C2H6NO2 for positive ion electrospray ionisation (PIESI) mode (m/z 76.0393) and C3H5O3 for negative ion electrospray ionisation (NIESI) mode (m/z 89.0244). To enhance calibration stability, lock-mass correction was also applied to each analytical run using these ubiquitous low-mass contaminants. A set of authentic standards was run prior to the sample set for each experiment.
Metabolomics data analysis
RAW spectra were converted to mzXML files (mzML files for fragmentation data) using XCMS for untargeted peak detection [120]. The resultant files were further processed using mzMatch [121] for peak matching and annotation, resulting in a tabular output that was analysed using IDEOM with default settings [122]. For stable-isotope assisted metabolomics experiments, mzMatch output (in .peakml format) was analysed using mzMatch-ISO to extract all carbon isotopologue abundances from putative metabolites [123]. Data analysis of stable isotope-labelled metabolomics was based on a 48 hour time-point in all experiments. Data was further analysed using Microsoft Excel or Metaboanalyst v4.0 [124]. The mzXML files from all metabolomics analyses are available in Metabolights.
RNA sequencing and data processing
RNA sequencing was carried out by Edinburgh Genomics (Edinburgh, UK). Libraries were prepared from 8 samples (4× T. brucei, 4× T. congolense) using the TruSeq Stranded mRNA kit (Illumina) and 2 × 75 bp paired-end sequencing was carried out using a HiSeq 4000 system (Illumina). Sequencing reads were aligned to the corresponding genome sequence using HiSat2 (--no-spliced-alignment) [125]. For T. brucei, the TREU 927 reference genome sequence was used (v34.0 from TriTrypDB [126]), whilst a PacBio assembly of T. congolense IL3000 was used for T. congolense [65]. The resulting SAM files were converted to BAM files using samtools [127], and subsequently filtered for quality and primary alignment (-q 1 −F 0×100), the latter to reduce the effects of multimapping. Read counts were extracted from the filtered BAM files using HTSeq-count (-s reverse -f bam -t CDS -i ID -m union -a 0 --nonunique all).
For all samples, transcripts per million (TPM) values for each gene were calculated manually using Microsoft Excel as follows: 1) Reads per kilobase (RPK) were calculated by dividing the read counts by the length of gene in kilobases; 2) All RPK values in a sample were summed and divided by 1 million as a scaling factor; 3) Each RPK value was divided by the scaling factor to yield TPM values [53]. To compare transcript abundances between the two species, Orthofinder [54] was used to infer orthologue genes or gene groups. Default parameters were used to compare the TriTrypDB v34.0 TREU 927 annotated proteins and the PacBio T. congolense IL3000 annotated proteins (S2 Table). A custom MATLAB (version R2019a) was used to combine the Orthofinder dataset and the TPM values for 1-to-1 orthologues, as well as “sum of TPM” values for groups containing multiple genes, where TPM value for each gene was summed, resulting in a final dataset (S1 Table). Raw RNA-seq data is deposited at GEO. Transcriptomics data were cross-referenced with the TrypanoCyc database (vm-trypanocyc.toulouse.inra.fr/; [60]) to enable pathway analysis of the data.
Computation
Figures were generated using Graphpad Prism version 8.4.0 (www.graphpad.com) with the exception of scatter plots and heatmaps, which were generated using R [128]. Heatmaps were generated using the R packages pheatmap and ComplexHeatmap [129]; scatter plots were generated using GGplot2 and GGally; and pathway maps were generated with Inkscape v1.0.
Supplementary Data
S1 Table: RNAseq dataset – T. congolense ex vivo, T. congolense in vitro, T. brucei ex vivo,
T. brucei in vitro, Silvester et al dataset
S2 Table: Orthofinder output comparing T. congolense TriTrypDB (v34.0), T. congolense
Liverpool pacbio, T. brucei TriTrypDB (v34.0) and other trypanosomatids
S3 Table: RNAseq dataset – T. congolense only, Pacbio assembly, single genes.
S4 Table: Supernatant metabolomics dataset for in vitro cultured T. congolense over a period of 56 hours. Metabolites highlighted in yellow were confidently predicted using a set of metabolite standards run alongside the experimental samples. Results of statistical analysis by means of a one-way repeated measures ANOVA (false discovery rate-adjusted P value, FDR) is also shown for metabolites that were taken forward for downstream analysis
S5 Table: TrypanoCyc pathways and linked Orthogroup gene IDs
S6 Table: Formulation of Steketee’s congolense medium (SCM)-6 & −7
S7 table: List of primers used in this study
Acknowledgements
The authors would like to thank the following people: Steve Kelly, Paul Michels & Simon Young for very useful discussion. We thank Anne-Marie Donachie for help with in vivo experiments. In addition, the authors would like to thank the following institutes: Glasgow Polyomics for LC-MS work, Edinburgh Genomics for RNAseq, MRC PPU DNA Sequencing and Services, Dundee, for plasmid sequencing. LM, PS, EP, HdK and MPB were funded by BBSRC grant BB/N007492/1, and LM, PS, EP, RR and MPB by BB/S00243X/1. CG and BW were funded by University of Nottingham Strategic Support Funds (Wellcome Trust), and GAM by Sir Halley Stewart Medical Research Grant (R410). This article is based on research funded in part by the Bill & Melinda Gates Foundation (Investment ID OPP1176784) and with UK aid from the UK Government (Project 300504) through GALVmed. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Bill & Melinda Gates Foundation or the UK Government. The Roslin Institute is core funded by the BBSRC (BS/E/D/20002173).
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