Trypanosoma cruzi amastigote transcriptome analysis reveals heterogenous populations with replicating and dormant parasites

doi:10.21203/rs.3.rs-3128778/v1

Trypanosoma cruzi is a protozoan parasite causing Chagas disease, with a complex life cycle involving different stages in insect vectors and mammalian hosts. Amastigotes are an intracellular form that replicates in the cytoplasm of host cells, and recent studies suggested that dormant forms may be contributing to parasite persistence, suggesting cellular heterogeneity among amastigotes. We investigated here if a transcriptomic approach could identify some heterogeneity in intracellular amastigotes and identify a dormant population. We used gene expression data derived from bulk RNA-sequencing of T. cruzi infection of human fibrobasts for deconvolution using CDSeq, which allows to simultaneously estimate amastigote cell-type proportions and cell-type-specific expression profiles. Six amastigote subpopulations were identified, confirming intracellular amastigotes heterogeneity, and one population presented characteristics of non-replicative dormant parasites, based on replication markers and TcRAD51 expression. Transcriptomic approaches appear to be powerful to understand T. cruzi cell differentiation and expansion of these studies could provide further insight on the role different cell types in parasite persistence and Chagas disease pathogenesis.

Biological sciences/Microbiology

Health sciences/Diseases/Infectious diseases

Amastigote

dormant

replication

RNA-seq

deconvolution

pathogenesis

Chagas disease

Trypanosoma cruzi is a protozoan parasite causing Chagas disease, a major neglected tropical disease in the Americas. The parasite is transmitted in the feces of hematophagous triatomine vectors when they blood-feed. There are at least 6 million cases of T. cruzi infection in the continent¹, of which 30-40% will develop chronic cardiomyopathy or digestive disease, often decades after the infection². Disease progression likely results from an imbalance of the multiple host-parasite interactions during infection, but the detailed mechanisms of pathogenesis are still poorly understood.

The parasite has a complex life cycle and transitions through different stages in both the insect vector and mammalian hosts, which adds further complexity to T. cruzi pathogenesis^3-5. Metacyclic trypomastigotes are the infective flagellated parasite form that differentiates in the rectum of triatomine vectors and can enter mammalian hosts through open skin or mucosal surfaces, initiating infection. Trypomastigotes are then able to invade host cells, where they differentiate into intracytoplasmic amastigotes. These amastigotes undergo extensive replication before differentiating into trypomastigotes which egress by rupturing the host cell and disperse throughout the host to infect new cells⁶. A major structural reorganization of parasite cells has been described during amastigogenesis⁷, together with changes in transcriptomic and proteomic profiles^3,8-10.

However, recent work indicated that some amastigotes could enter a dormant state with reduced replicative and metabolic activity, and this process has been specifically involved in drug escape by the parasite^11-13. This suggests some level of cellular heterogeneity among amastigotes, including intermediate forms in the differentiation process, in agreement with their asynchronous replication¹⁴. Dormancy seems to be spontaneous in all T. cruzi parasite strains tested, although strain-specific differences have been observed, at least in vitro, with dormancy affecting from 0.2% of amastigotes for the Y strain (TcII discrete typing unit (DTU)) up to 7% for Bug2148 strain (TcV DTU)¹⁵. Thus, it has been proposed that parasite strains presenting a high percentage of dormancy would be more prone to persist in hosts and establish chronic infections. However, the current understanding of the mechanisms of entry into dormancy, or in the reactivation of dormant amastigotes is limited¹².

TcRAD51, a protein involved in DNA repair and homologous recombination¹⁶, was found to be directly associated with dormancy, and single TcRAD51 knock-out parasites present reduced dormancy in vitro¹⁵. However, it is likely that additional genes and pathways are involved in the induction of T. cruzi dormancy, and their characterization will be key to better understand this process. Also, the level of heterogeneity among amastigotes, and its relevance to T. cruzi cell cycle and pathogenesis remain largely unknown. As a first step to address these issues, we investigated here if a transcriptomic approach can identify functional heterogeneity in intracellular amastigotes and identify a dormant amastigote population. Indeed, such approaches have been successfully used to investigate dormancy in Plasmodium parasites¹⁷ and can led to key insights into the mechanisms leading to entry into dormancy and of T. cruzi pathogenesis.

Amastigote population heterogeneity

Transcriptomic approaches have been used to assess T. cruzi stage-specific gene expression profiles^3,8-10. Here, we focused on amastigote gene expression profile during infection of human fibroblasts, from 4 to 72h post-infection (Figure 1), using a well validated data set based on RNA-sequencing⁸. We used CDSeq for the deconvolution of gene expression data from bulk RNA-sequencing of these cells to simultaneously estimate amastigote cell-type proportions and their specific gene expression profiles. Deconvolution revealed that amastigotes were not a homogenous cell type, but rather a collection of cells presenting heterogenous transcription profiles. The best posterior distribution indicated six subpopulations of amastigotes (Figure 2A), which was thus selected for further analysis. Five of six of these amastigote subpopulations were rather abundant and expanded over time, accounting for 10-20% of the amastigotes each, while one subpopulation (labeled as B) accounted for only 2-5% of all amastigotes and was constantly detected (Figure 2B). This small population of amastigote was also non-replicative, while all other populations replicated at different rates, the most replicative being populations A and F (Figure 2C).

Functional properties of amastigote populations

We then assessed functional properties of amastigote populations by analyzing their respective gene expression profiles. Expression data from 6,834 genes comprised the expression profile of amastigotes. As shown in Figure 3, there was a good clustering of samples from each population at each time point, based on principal component analysis (PCA) of gene expression data, although the best clustering was observed at 12 and 24h post-infection. The non-replicative population B clustered particularly well apart from the others at all time points. These transcriptomic differences suggested potential functional differences.

To further characterize these amastigote subpopulations, we focused on the expression levels of PUF-9 (TcCLB.506563.10), Histone hairpin RBP (TcCLB.511867.150), and cyclin 6 (TcCLB.507089.260), which are up-regulated in replicating T. cruzi parasites¹⁸. As shown in Figure 4A, B, C, most amastigote subpopulations presented elevated expression levels of these replication-associated genes, except subpopulation B, which presented low levels of expression of all three replication markers. These data are consistent with this specific amastigote subpopulation being non-replicative. We further analyzed the expression profile of TcRAD51 in these cells, as its expression is increased in dormant amastigotes ¹⁵, and found that it was over-expressed in amastigote subpopulation B compared to the other subpopulations (Figure 4D). Together, these data demonstrate that we were able to detect transcriptomic heterogeneity in T. cruzi amastigote cells, and that a specific subpopulation with dormant characteristics could be identified by deconvolution of bulk RNA-sequencing data.

We then focused on the identification of genes that were differentially expressed among amastigote populations. DESeq2 analysis indicated that there were 91 genes with at least a 1.5-fold difference in expression level among populations (false discovery rate (FDR)-adjusted P<0.05) (Supplementary Table 1). Pathway analysis further indicated that these genes were involved in multiple functional aspects of amastigote biology, highlighting the heterogeneity of these populations. As expected from the differences in replication rates shown above (Figure 2), underlying pathways associated with protein-DNA interactions, chromatin organization and remodeling, chromosome and nucleosome organization, and detection of cell density were identified (Table 1). In addition, multiple catabolic and biosynthesis pathways suggested broad metabolic differences among amastigote populations. Pathways associated with cell differentiation were also identified, including multivesicular body sorting pathway, cellular component assembly, biogenesis, and organization, organelle organization, ribosomal assembly, and macromolecule biosynthesis (Table 1). Finally, differences in signaling pathways including calcium and other secondary messenger signaling suggest different interactions with host cells (Table 1). Together, these data indicate broad structural and metabolic heterogeneity among amastigote populations, in addition to their differences in replication.

The replication and persistence of intracellular T. cruzi amastigotes is an important component of Chagas disease pathogenesis that is still poorly understood. The precise characterization of parasite differentiation processes and the role of different forms and stages have been lingering questions^5,6. While amastigote have been considered a rather homogenous population of replicating cells, the recent identification of non-replicative dormant amastigotes is challenging this view^11–13. In that respect, our re-analysis of amastigote transcriptomic profile is providing key evidence of amastigote cell heterogeneity, with up to six subpopulations identified by deconvolution of gene expression data. Importantly, these amastigote populations present different replicative properties, and include a small population (2–5% of total amastigotes) that is clearly non-replicative and likely corresponds to dormant cells. This was evidenced by cell count and replication rate estimates and the expression profile of replication markers (PUF-9, Histone hairpin RBP, and cyclin 6) and of a dormancy marker (TcRAD51).

Differential gene expression profiles further indicated multiple functional differences in metabolism and signaling among amastigote populations. While one population (population B) could clearly be associated with dormancy, the properties of each of the other five amastigote populations remain unclear. Two of these (population A and F) had the highest replication rates, while the other populations appeared to be initially replicative during the early hours of cell infection, but not at later time points. These different populations may represent amastigote-trypomastigote intermediate differentiation stages or intermediate within the amastigote replication cycle. Indeed, there is evidence that both replication and differentiation are asynchronous within individual infected host cells¹⁴, so such intermediates are expected. Yet, amastigote populations with new roles and fates during T. cruzi infection and pathogenesis cannot be ruled out. Importantly, our study points to transcriptomics as a powerful approach to characterize these amastigote populations, and a single-cell transcriptomic approach is poised to provide a clear description of amastigote populations. Such an approach has already been successfully used with Trypanosoma brucei blood and procyclic forms¹⁹.

Pathway analysis indicated that many functional properties differ among amastigote populations, including replication, cell metabolism and signaling. This level of difference within amastigotes is comparable to that observed among parasite stages, highlighting the complexity of the molecular interactions between the amastigotes and host cells. As noted before¹⁴, metabolic differences among T. cruzi cells may lead to heterogeneity in drug susceptibility. Indeed, the reduced metabolic activity of dormant amastigotes is thought to be specifically involved in drug escape by the parasite^11–13. Thus, further understanding of amastigote functional heterogeneity remains key for more effective treatments,

Dormancy in T. cruzi has been found to be closely associated with TcRAD51 expression¹⁵, which is further supported by our data. As this protein participates in DNA repair and recombination¹⁶, dormancy may favor the generation of recombinant parasites within host cells, which could contribute to parasite persistence over time. Also, further characterization of the transcriptomic profile of these dormant amastigotes may allow the identification of cell markers for a specific labeling of this population, which would allow to better characterize their role during infection.

In conclusion, our analysis shows that T. cruzi intracellular amastigotes are an heterogenous population with at least six cell types, and this heterogeneity should be taken into account to better understand parasite persistence in hosts and Chagas disease pathogenesis. Of particular interest, one of these population presented characteristics of non-replicative dormant parasites, which may play a key role during infection. Transcriptomic approaches appear to be powerful to investigate the T. cruzi cell differentiation. Single-cell RNA sequencing of amastigotes could provide further insight on their diversity and the role of each population in parasite persistence and Chagas disease pathogenesis.

T. cruzi transcriptome.

We used a previously published and well validated data set derived from RNA-sequencing of amastigotes from the Y strain (TcII) in human fibroblasts at multiple time points, ranging from 4h to 72h post infection⁸ (NCBI Bioproject PRJNA251582). This time-period covers newly differentiated amastigotes, to late-stage amastigotes before their cell egress (Figure 1), and 2-4 biological replicates per time points were available (Table 2). This data set was initially used to describe T. cruzi parasite stage-specific gene expression profiles, together with that of the infected host cells⁸.

Deconvolution of amastigote populations

CDSeq was used to perform unsupervised cell deconvolution of the bulk RNA-sequencing data²⁰ and evaluate the occurrence of different amastigote populations. It is a complete deconvolution method that uses only gene expression data from bulk RNA-sequencing of tissue samples to simultaneously estimate cell-type proportions and cell-type-specific expression profiles. Its main advantage is that it does not require pre-specified cell-type proportions or cell-type-specific expression profiles for the deconvolution process²⁰. In this case, marker gene sets can then be used to characterize the nature of the cell-types/population identified.

Raw read counts were used as the input for deconvolution analysis⁸. The CLBrener-Esmeraldo-like T. cruzi genome annotation data was used to provide gene length information, as an additional input for deconvolution analysis. CDSeq was run under developer recommended parameters. The most likely number of T. cruzi amastigote populations was selected based on the log posterior distribution as calculated in CDSeq²⁰. Principal component analysis (PCA) was performed to visualize overall gene expression profiles among samples and amastigote populations.

The relative proportions of the respective amastigote populations at each time point were adjusted according to the percentage of reads mapping to T. cruzi genome (Table 2), which was used as an indicator of the absolute number of amastigote cells and its changes over time. The replication rate of each amastigote population was calculated based on the estimated change in cell number between time points expressed per hour.

Functional properties of amastigote populations

The gene expression profile for each amastigote population provided by CDSeq deconvolution was used to identify the gene expression level of specific genes previously identified as involved in regulating T. cruzi cell cycle and replication. These included PUF-9 (TcCLB.506563.10), Histone hairpin RBP (TcCLB.511867.150), and cyclin 6 (TcCLB.507089.260), which are up-regulated in replicating T. cruzi parasites¹⁸. We further analyzed the expression profile of TcRAD51 in these amastigote populations, as its expression is increased in dormancy¹⁵.

Finally, we used DESeq2²¹ to identify differentially expressed genes among amastigote population based on the CDSeq expression profile. We used a threshold of 1.5-fold change with a statistical significance of 0.05 with false-discovery rate (FDR)-adjusted P values. Significant differentially expressed genes were then used for pathway analysis using the TriTrypDB and REVIGO web server²² to summarize Gene Ontology terms and assess potential functional differences among amastigote populations.

Authors contribution

Conceptualization: ED and CH

Methodology: HD, CH and ED

Formal analysis and investigation: HD

Writing original draft: ED

Reviewing and editing: HD and CH

Final approval: HD, CH and ED

Data availability statement

Data are available in NCBI Bioproject PRJNA251582 and Li, Y. et al. Transcriptome Remodeling in Trypanosoma cruzi and Human Cells during Intracellular Infection. PLoS pathogens 12, e1005511 (2016).

Competing Interests Statement

The authors declare to have no conflict of interest.

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Table 1. GO pathways of differentially expressed genes of amastigote populations

GO term	Name	LogSize	Frequency	Group
GO:0046176	aldonic acid catabolic process	3.897	0.026	Blue
GO:0019520	aldonic acid metabolic process	4.327	0.070	Blue
GO:0009102	biotin biosynthetic process	4.323	0.070	Blue
GO:0006768	biotin metabolic process	4.323	0.070	Blue
GO:0046394	carboxylic acid biosynthetic process	6.085	4.032	Blue
GO:0044283	small molecule biosynthetic process	6.250	5.899	Blue
GO:0044249	cellular biosynthetic process	6.889	25.681	Green
GO:0034645	cellular macromolecule biosynthetic process	6.324	6.991	Green
GO:0006423	cysteinyl-tRNA aminoacylation	4.081	0.040	Green
GO:0010467	gene expression	6.693	16.353	Green
GO:0009100	glycoprotein metabolic process	5.309	0.675	Green
GO:0009059	macromolecule biosynthetic process	6.652	14.863	Green
GO:0043413	macromolecule glycosylation	5.267	0.613	Green
GO:0000460	maturation of 5.8S rRNA	4.109	0.043	Green
GO:0006777	Mo-molybdopterin cofactor biosynthetic process	4.808	0.213	Green
GO:0034660	ncRNA metabolic process	6.048	3.704	Green
GO:0090304	nucleic acid metabolic process	6.755	18.873	Green
GO:1901576	organic substance biosynthetic process	6.902	26.447	Green
GO:1901566	organonitrogen compound biosynthetic process	6.635	14.308	Green
GO:0008612	peptidyl-lysine modification to peptidyl-hypusine	3.785	0.020	Green
GO:0018209	peptidyl-serine modification	4.165	0.049	Green
GO:0018105	peptidyl-serine phosphorylation	4.133	0.045	Green
GO:0051189	prosthetic group metabolic process	4.813	0.216	Green
GO:0016070	RNA metabolic process	6.595	13.042	Green
GO:0006396	RNA processing	6.081	3.993	Green
GO:0016072	rRNA metabolic process	5.543	1.158	Green
GO:0016043	cellular component organization	-	6.372	None
GO:0046177	D-gluconate catabolic process	-	3.662	None
GO:0019521	D-gluconate metabolic process	-	4.192	None
GO:0060245	detection of cell density	-	3.767	None
GO:0009101	glycoprotein biosynthetic process	-	5.287	None
GO:0019720	Mo-molybdopterin cofactor metabolic process	-	4.808	None
GO:0043545	molybdopterin cofactor metabolic process	-	4.810	None
GO:0072330	monocarboxylic acid biosynthetic process	-	5.476	None
GO:0006334	nucleosome assembly	-	4.435	None
GO:0034728	nucleosome organization	-	4.453	None
GO:0016053	organic acid biosynthetic process	-	6.095	None
GO:0006486	protein glycosylation	-	5.267	None
GO:0065004	protein-DNA complex assembly	-	4.783	None
GO:0070085	glycosylation	5.348	0.739	Orange
GO:0015877	biopterin transport	0.778	0.000	Peach
GO:0071985	multivesicular body sorting pathway	4.308	0.067	Peach
GO:0019722	calcium-mediated signaling	4.309	0.067	Purple
GO:0009595	detection of biotic stimulus	3.840	0.023	Purple
GO:0051606	detection of stimulus	5.188	0.512	Purple
GO:0009372	quorum sensing	3.736	0.018	Purple
GO:0019932	second-messenger-mediated signaling	4.440	0.091	Purple
GO:0022607	cellular component assembly	5.903	2.654	Red
GO:0044085	cellular component biogenesis	6.165	4.846	Red
GO:0006325	chromatin organization	5.406	0.844	Red
GO:0006338	chromatin remodeling	5.226	0.558	Red
GO:0051276	chromosome organization	5.569	1.230	Red
GO:0071103	DNA conformation change	5.376	0.789	Red
GO:0006996	organelle organization	6.048	3.703	Red
GO:0065003	protein-containing complex assembly	-	5.652	Red
GO:0043933	protein-containing complex organization	5.717	1.728	Red
GO:0071824	protein-DNA complex subunit organization	4.793	0.206	Red
GO:0000027	ribosomal large subunit assembly	4.460	0.096	Red
GO:0009987	cellular process	7.385	80.395	Salmon
GO:0009058	biosynthetic process	6.920	27.562	Teal
GO:0044237	cellular metabolic process	7.193	51.657	Teal
GO:0034641	cellular nitrogen compound metabolic process	6.959	30.146	Teal
GO:0046483	heterocycle metabolic process	6.903	26.513	Teal
GO:0043170	macromolecule metabolic process	7.060	38.107	Teal
GO:0006807	nitrogen compound metabolic process	7.168	48.787	Teal
GO:1901360	organic cyclic compound metabolic process	6.917	27.369	Teal
GO:0044238	primary metabolic process	7.208	53.491	Teal
GO:0071840	cellular component organization or biogenesis	6.455	9.457	Violet

Table 2. Transcriptomic data used

Developmental stage	Accession Number	Number of reads that pass Illumina filter	Total number of reads mapped	% of total reads mapped	Reads mapped to T. cruzi	% of mapped reads belonging to T. cruzi
	SRR1346027	139,558,460	130,016,017	93.16%	2,585,633	1.99%
Amastigote	SRR1346028	123,249,854	81,724,984	66.31%	2,257,327	2.76%
4 hpi	SRR1346029	98,909,298	94,669,006	95.71%	2,928,987	3.09%
	SRR1346031	157,401,226	148,513,778	94.35%	3,128,883	2.11%
Amastigote	SRR1346032	112,249,358	106,802,654	95.15%	2,014,693	1.89%
6 hpi	SRR1346033	97,411,582	91,909,631	94.35%	2,811,907	3.06%
Amastigote	SRR1346035	88,441,820	83,974,766	94.95%	1,769,313	2.11%
12 hpi	SRR1346036	93,933,948	89,531,503	95.31%	2,136,351	2.39%
	SRR1346038	88,843,990	84,786,038	95.43%	4,635,117	5.47%
Amastigote	SRR1346039	79,347,540	73,605,848	92.76%	3,903,274	5.30%
24 hpi	SRR1346040	74,297,462	70,880,898	95.40%	4,982,378	7.03%
	SRR1346044	57,701,782	52,398,585	90.81%	6,866,656	13.10%
Amastigote	SRR1346045	57,692,178	52,602,786	91.18%	6,985,398	13.28%
48 hpi	SRR1346046	77,919,340	70,119,342	89.99%	13,138,673	18.74%
	SRR1346047	76,483,856	67,999,152	88.91%	19,099,189	28.09%
	SRR1346050	49,143,458	40,315,329	82.04%	15,056,971	37.35%
Amastigote	SRR1346051	65,873,648	54,571,365	82.84%	19,546,061	35.82%
72 hpi	SRR1346052	90,450,622	87,107,335	96.30%	8,327,776	9.56%

Data from ⁸

No competing interests reported.

SupplementaryTable1.xlsx

Trypanosoma cruzi amastigote transcriptome analysis reveals heterogenous populations with replicating and dormant parasites

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