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Nature Communications volume 13, número do artigo: 5326 (2022) Citar este artigo

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Os tripanossomatídeos, que incluem os principais patógenos de humanos e animais, são protozoários flagelados para os quais o ciclo celular é controlado e os mecanismos subjacentes não são completamente compreendidos. Aqui, descrevemos uma tela de biblioteca de interferência de RNA em todo o genoma para defeitos do ciclo celular em Trypanosoma brucei. Induzimos knockdown paralelo massivo, classificamos a população perturbada usando citometria de fluxo de alto rendimento, alvos de RNAi sequenciados profundamente de cada estágio e perfis de ciclo celular reconstruídos digitalmente em escala genômica; possibilitando também a visualização de dados por meio de uma ferramenta online (https://tryp-cycle.pages.dev/). A análise de várias centenas de genes que impactam a progressão do ciclo celular revela> 100 knockdowns de componentes flagelares ligados à endorreduplicação do genoma, evidências de controle metabólico da transição G1-S, knockdowns de proteínas de ligação ao mRNA reguladoras de antígeno de superfície ligados ao acúmulo de G2M e uma suposta nucleoredoxina necessária tanto para a segregação do genoma mitocondrial quanto para a mitose. Os resultados fornecem evidências genômicas funcionais abrangentes para os mecanismos, vias e reguladores conhecidos e novos que coordenam a progressão do ciclo celular do tripanossoma.

O ciclo celular eucariótico canônico abrange fases discretas: G1 (gap 1), quando a célula se prepara para a replicação do DNA; Fase S (síntese), quando ocorre a replicação do DNA nuclear; G2 (gap 2), quando a célula se prepara para a mitose; e M (mitose) quando o DNA replicado é segregado e o núcleo se divide1. A mitose é seguida de citocinese (divisão celular), gerando duas células-filhas2. Os mecanismos de limitação de taxa que facilitam o controle de qualidade são acionados em pontos discretos. Assim, as anomalias que ocorrem durante a progressão do ciclo celular podem resultar num atraso ou paragem do ciclo celular, para permitir que a célula resolva a anomalia; na morte celular, se a anomalia não puder ser resolvida ou, entre outros desfechos, na carcinogênese. Portanto, a progressão ao longo do ciclo celular está normalmente sob estrito controle de pontos de verificação; os pontos de verificação G1-S, fase intra S, G2-M e fuso controlam o início da fase S, a progressão da fase S, o início da fase M e a progressão da fase M, respectivamente3. Esses processos têm sido extensivamente estudados, principalmente porque os defeitos do ciclo celular são gatilhos comuns para a carcinogênese4. No entanto, a nossa compreensão da evolução e dos mecanismos de controlo da progressão do ciclo celular eucariótico deriva principalmente de estudos sobre os opistocontes (incluindo animais e fungos), com relativamente menos estudos sobre eucariotas divergentes, como os tripanosomatídeos .

Os tripanossomatídeos são protozoários flagelados e incluem parasitas que causam uma série de doenças tropicais negligenciadas que têm grandes impactos na saúde humana e animal. O tripanossoma africano, Trypanosoma brucei, é transmitido pela mosca tsé-tsé e causa doenças humanas e animais, doença do sono e nagana, respectivamente, em toda a África Subsaariana5. T. brucei emergiu como um sistema experimental altamente tratável, tanto como parasita quanto como organismo modelo6. Por exemplo, o flagelo do T. brucei7 serve de modelo para estudos sobre ciliopatias humanas8,9,10,11. Características divergentes, compartilhadas com outros tripanossomatídeos patogênicos, como Trypanosoma cruzi e Leishmania, incluem glicólise compartimentada em glicossomos12, uma única mitocôndria com uma estrutura complexa de DNA mitocondrial conhecida como cinetoplasto13 e transcrição policistrônica de quase todos os genes14. A transcrição policistrônica generalizada e constitutiva em tripanossomatídeos dá grande ênfase aos controles pós-transcricionais por proteínas de ligação ao mRNA (RBPs) e controles pós-traducionais, envolvendo a fosforilação de proteínas, por exemplo.

Estudos que enfocam o controle do ciclo celular em T. brucei revelaram características conservadas com outros eucariotos bem estudados, mas também características divergentes . Notavelmente, as evidências disponíveis sugerem que certos pontos de verificação do ciclo celular estão ausentes. Por exemplo, a citocinese pode ocorrer independentemente da mitose ou da síntese de DNA nuclear no estágio de inseto de T. brucei16. Além disso, funções anteriormente consideradas cumpridas por proteínas altamente conservadas empregam proteínas específicas de linhagem ou altamente divergentes em tripanossomatídeos. O complexo cinetocoro, que dirige a segregação cromossômica, é específico dos tripanossomatídeos, por exemplo, enquanto o complexo de reconhecimento de origem (ORC), envolvido na iniciação da replicação do DNA, é altamente divergente. Em termos de estudos de alto rendimento, o monitoramento do transcriptoma19 e do proteoma20 durante o ciclo celular de T. brucei revelou centenas de mRNAs e proteínas regulados, enquanto a análise fosfoproteômica revelou fosforilação dinâmica de vários RBPs21. A divergência apresenta desafios pendentes substanciais, no entanto, uma vez que muitos genes de T. brucei ainda não receberam uma função específica, e muitos reguladores do ciclo celular provavelmente ainda precisam ser identificados. Triagens genéticas funcionais de alto rendimento em escala genômica podem ser usadas para avaliar simultaneamente cada gene em um genoma para uma função em um processo específico. Desenvolvemos sequenciamento de alvo de interferência de RNA (RIT-seq) para T. brucei e geramos previamente perfis de aptidão em escala genômica, facilitando previsões de essencialidade e a priorização de potenciais alvos de medicamentos .

4 C) cells (Fig. 1a). Polyploid cells arise due to endoreduplication, additional rounds of DNA replication without cytokinesis, either with24 or without25,26 mitosis, yielding cells with multiple nuclei or with polyploid nuclei, respectively./p>4 C (multiple nuclei) phenotypes; anuclear zoids are not shown as they are undetectable by RIT-seq. b The schematic illustrates the RIT-seq screen; massive parallel induction of RNAi with tetracycline (Tet), followed by flow cytometry and RIT-seq, allowing for reconstruction of cell cycle profiles, using mapped reads from each knockdown. Each read-mapping profile encompasses the gene of interest and associated untranslated regions present in the cognate mRNA. The library data represents the uninduced and unsorted population. GeneIDs, Tb927.7.3160 for example, are indicated without the common ‘Tb927.’ component./p>4 C) pools (Supplementary Fig. 1). Fixation and staining with the fluorescent DNA intercalating dye were pre-optimised for high-throughput sorting (see Materials and Methods). Approximately 10 million cells were collected for each of the G1, S and G2M pools and samples from these pools were checked post-sorting to assess their purity (Fig. 1b, Supplementary Fig. 1). For the perturbed and less abundant <2 C and >4 C pools, less than one million cells were collected; these pools were retained in their entirety for RIT-seq analysis./p>7200 non-redundant gene sequences in the uninduced and induced, unsorted library controls and in each of the five sorted samples. We selected the 24 h timepoint, equivalent to approximately 3.5 population doubling times, for the current analysis. We found that reads for 23.4% of genes were diminished by >3-fold following 72 h of knockdown in our prior RIT-seq study23, while reads for only 0.6% of genes dropped by >3-fold following 24 h of knockdown in the unsorted control samples analysed here (see Supplementary Fig. 2a, b). Thus, 24 h should have allowed sufficient time for the development of robust inducible phenotypes and also captured perturbed cells before they were critically diminished due to loss-of-fitness. An unanticipated feature that emerged from this analysis of prior RIT-seq data was that knockdown of proteins associated with DNA replication typically failed to register a major loss-of-fitness (Supplementary Fig. 2a, b). This suggested that a reduced rate of DNA replication can be tolerated, albeit extending S phase (see below) but having relatively little impact on viability. Each sorted sample library yielded between 23 and 37 million mapped read-pairs; <2 C = 37 M, G1 = 35 M, S = 30 M, G2M = 23 M, > 4 C = 25 M; this set of five samples yielded data for >7000 genes which equates to >35,000 RNAi data-points (Supplementary data 1)./p>4 C overrepresented, following knockdown (Fig. 1b). These outputs suggest that loss of a cytoplasmic dynein heavy chain (7.3160) does not perturb cell cycle distribution; that the proteasome is required to complete G2M (see below); and that knockdown of a flagellar axonemal dynein heavy chain (11.11220) results in endoreduplication in the absence of cytokinesis; dyneins are cytoskeletal motor proteins that either move along microtubules or drive microtubule sliding, to produce a flagellar beat, for example30./p>4 C cells, indicating endoreduplication, which yielded 284 genes (Fig. 2a, left-hand panel; Supplementary data 1). The >4 C phenotype was previously observed following α-tubulin knockdown in a landmark study that first described RNAi in T. brucei24 and, indeed, we observed pronounced overrepresentation of >4 C cells for both adjacent α-tubulin and β-tubulin gene knockdowns (Fig. 2a, middle and right-hand panel). We then examined knockdowns reporting an overrepresentation of <2 C cells, indicating a reduced DNA content, which yielded 10 hits (Fig. 2b, left-hand panel; Supplementary data 1). Haploid cells were previously observed following DOT1A knockdown31 and, consistent with the previous report, we observed pronounced overrepresentation of <2 C cells for the DOT1A gene knockdown (Fig. 2b, middle and right-hand panel); we are not aware of other knockdowns reported to yield a similar phenotype. Indeed, other ‘<2 C hits’ mostly encode small hypothetical proteins, seven of which are 73 ± 11% shorter than the average, consistent with low read-count and under-sampling for these hits (Supplementary Fig. 2c). The remaining two hits are a histone chaperone (ASF1B) and a glycolytic enzyme (PFK). Together, these results provided initial validation for the >4 C and <2 C components of the screen./p>4 C experiment in red; those with reads in the >4 C pool that exceeded the mean fold-change value by >1.75 times the SD, equivalent to >1.117-fold the sum of reads in the G1, S phase and G2M samples combined. The read-mapping profile and read-counts for α/β-tubulin are shown to the right. b The plot on the left shows knockdowns overrepresented in the sub-2C experiment in orange; those with reads in the sub-2C pool that exceeded the mean fold-change value by >1.75 times the SD, equivalent to >4-fold the sum of reads in the G1, S phase and G2M samples combined. The read-mapping profile and read-counts for DOT1A are shown to the right. c The RadViz plot shows knockdowns that registered >25% overrepresented read-counts in the G1 (purple), S phase (green), or G2M (blue) categories. d Read-mapping profiles and relative read-counts for example hits. PCNA, proliferating cell nuclear antigen; PPL2, PrimPol-like 2. e The Venn diagram shows the distribution of knockdowns overrepresented in each arm of the screen./p>25% overrepresented read counts in each of these categories are highlighted in the RadViz plot in Fig. 2c (also see Supplementary data 1) and data for an example from each category are shown in Fig. 2d; the glycolytic enzyme, aldolase, reported 104% increase in G1 cells (further details below); the proliferating cell nuclear antigen (PCNA), a DNA sliding clamp that is a central component of the replication machinery32, reported 25% increase in S phase cells and 13% increase in G2M cells, consistent with prior analysis33; and PrimPol-like 2 (PPL2), a post-replication translesion polymerase, reported 65% increase in G2M cells, also consistent with prior analysis34. These results provided initial validation for the G1, S phase and G2M components of the screen. The full dataset can be searched and browsed using an interactive, open access, online data visualization tool (see Supplementary Fig. 3; https://tryp-cycle.pages.dev/)./p>4 C, p = 9.4−213), consistent with loss-of-fitness as a common outcome following a cell cycle progression defect. Taken together, the analyses above provided validation for the RIT-seq based cell cycle phenotyping approach and yielded >1000 candidate proteins that impact progression through specific steps of the T. brucei cell cycle./p>4 C cells can arise due to endoreduplication without cytokinesis, either with24 or without25,26 mitosis. Endoreduplication defects were previously observed following knockdown of α-tubulin24 or flagellar proteins7,35; consistent with the view that flagellar beat is required for cytokinesis in bloodstream form T. brucei. As shown above, dynein heavy chain (see Fig. 1b), α-tubulin and β-tubulin (see Fig. 2a) knockdowns were amongst 284 knockdowns overrepresented in the endoreduplicated pool in our screen. Gene Ontology (GO) annotations, which provide structured descriptions of gene products in terms of functions, processes, and compartments, were assessed to further profile this cohort of knockdowns. Terms overrepresented in association with an endoreduplication defect included ‘dynein’, ‘intraflagellar transport’ (IFT), ‘axoneme’ and ‘cytoskeleton’, and also ‘chaperonin T-complex’, ‘cytokinesis’ and ‘cell cycle’ (Fig. 3a). The violin plot in Fig. 3b shows specific enrichment of IFT and dynein knockdowns in association with endoreduplication. Exocyst components, primarily involved in exocytosis36, were included as a control cohort since none of the exocyst components registered enrichment in the >4 C pool, nor in any other experimental pool analysed here (see below). Enrichment of individual chaperonin T-complex components, dyneins, and IFT factors in the >4 C pool is illustrated in Fig. 3c. The chaperonin T-complex is involved in tubulin and actin folding37 and, notably, actin knockdown was also associated with endoreduplication (Supplementary Fig. 4)./p>4 C hits, those that exceed the mean fold-change value in this set by >1.75 times the SD. P-values are shown on the right. b The violin plot shows relative >4 C read-counts for cohorts of genes and reflects data distribution. Open circles indicate median values and the vertical bars indicate 95% confidence intervals. Significantly overrepresented cohorts are indicated in red. c The plots show overrepresentation of T-complex, dynein and intraflagellar transport (IFT) factors in red in the >4 C experiment. d The heatmaps show relative representation in all five sorted pools for the above and additional cohorts of knockdowns; blue, most overrepresented. e Example read-mapping profiles for hits overrepresented in the >4 C pool. f Example read-mapping profiles for ciliopathy-associated hits overrepresented in the >4 C pool. CMF Component of Motile Flagella, CFAP Cilia and Flagella Associated Protein./p>4 C pool; these include additional dynein chains, radial spoke proteins, extra-axonemal paraflagellar rod (PFR) proteins, as well as nucleoporins. The gallery in Fig. 3e shows examples of RIT-seq read-mapping profiles for twenty-six individual genes that register >4 C enrichment following knockdown. In addition to the categories above, these include the inner arm dynein 5-138, FAZ proteins which mediate attachment of the flagellum to the cell body39; all four cytokinesis initiation factors CIF1-440, and chromosomal passenger complex components, including CPC1 and the aurora B kinase, AUK1. AUK1 and CPC1 are spindle-associated and regulate mitosis and cytokinesis26,41. Notably, endoreduplication was reported previously following AUK1 knockdown in bloodstream form T. brucei42 and this is the kinase with the most pronounced overrepresentation in our >4 C dataset. The next >4 C overrepresented kinase is the CMGC/RCK (Tb927.3.690), knockdown of which previously yielded a striking cytokinesis defect43./p>4 C overrepresentation include the centriole cartwheel protein SAS644, the cleavage furrow-localizing protein FRW145, the basal body—axoneme transition zone protein TZP12546 and the basal body protein BBP24847. One hundred additional examples are shown in Supplementary Fig. 4, including intermediate and light chain dyneins, other flagellum-associated factors, radial spoke proteins, components of motile flagella, flagellum attachment and transition zone proteins, kinesins48,49, nucleoporins50, and many previously uncharacterised hypothetical proteins. Some other notable examples include the microtubule-severing katanin KAT8051, the dynein regulatory factor trypanin52, the AIR9 microtubule associated protein53, CAP51V54 and importin, IMP155./p>4 C pool are shown in Fig. 3f and Supplementary Fig. 4. These include orthologues of proteins linked to primary ciliary dyskinesia (DNAH5, DNAH11, RSPH4 and DNAI1)11; male infertility (PF16, PACRGA, CFAP43 and CMF7/TbCFAP44)7,10; and cone-rod dystrophies, as well as other ocular defects (CMF17, CMF39 and CMF46)8./p>4 C pool, we conclude that RIT-seq screening provided comprehensive genome-scale identification of cytokinesis defects in bloodstream form T. brucei. Endoreduplication appears to be a common outcome following a cytokinesis defect. Amongst hundreds of genes required for progression through cytokinesis, flagellar proteins featured prominently, including the majority of dynein chains and intraflagellar transport factors. Many of these factors are essential for viability and include potential druggable targets in trypanosomatids, as well as orthologues of proteins associated with ciliopathies./p>25% overrepresented read counts in each of these categories (Fig. 2c, e). GO annotations within each cohort revealed a number of enriched terms (Fig. 4a). Overrepresented knockdowns were associated with glycolysis, mRNA binding and the mitochondrion in the G1 pool, with DNA replication in the S phase pool and with a broadly similar profile to that seen for the >4 C set in the G2M pool./p>25% overrepresented read-count in each of these categories. P-values are shown on the right. b The violin plots show relative G1, S phase or G2M read-counts for cohorts of genes and reflect data distribution. Open circles indicate median values and the vertical bars indicate 95% confidence intervals. Overrepresented cohorts are indicated in purple, green and blue, respectively. IFT intraflagellar transport. c The heatmaps show relative representation in all five sorted pools for the above and additional cohorts of knockdowns; blue, most overrepresented. MCM minichromosome maintenance, PSP1 DNA polymerase suppressor 1./p>4 C pools likely reflects cytokinesis defects with cells accumulating both before and after endoreduplication; compare G2M and >4 C data for IFT factors and dyneins in Fig. 4b and Fig. 3b, for example. Other mitosis or cytokinesis-perturbed phenotypes are likely not associated with substantial endoreduplication; see the kinetochore and proteasome cohorts in Fig. 4b, for example. Once again, the exocyst provided a control cohort with no components registering enrichment in the G1, S phase or G2M pools following knockdown (Fig. 4b)./p>25% overrepresentation in the G1 pool; hexokinase, phosphofructokinase, aldolase (see Fig. 2c), triosephosphate isomerase, glyceraldehyde 3-phosphate dehydrogenase, phosphoglycerate kinase C and pyruvate kinase. Glycolysis operates in peroxisome-like organelles known as glycosomes in trypanosomes and is thought to be the single source of ATP in bloodstream form cells12. Glycolysis also provides metabolic intermediates that support nucleotide production. Notably, mammalian cell proliferation is accompanied by activation of glycolysis, and the Warburg effect relates to this phenomenon in oncology60,61. Indeed, hexokinase regulates the G1/S checkpoint in tumour cells62. The results are also consistent with the observation that T. brucei accumulate in G1 or G0 under growth-limiting conditions63 or during differentiation to the non-dividing stumpy form64, possibly reflecting a role for glucose sensing in differentiation65. Notably, glycolytic enzymes are downregulated 6.7 + /−5.2-fold in stumpy-form cells66. We conclude that, as in other organisms67, there is metabolic control of the cell cycle and a nutrient sensitive restriction point in T. brucei, with glycolysis playing a role in the G1 to S phase transition and possibly also the G1/G0 transition./p>25% overrepresented read-counts in the G1 category are indicated. Black data-points indicate other genes from each cohort. Grey data-points indicate all other genes. The read-mapping profiles and relative read-counts in the lower panel show example hits. b As in a but for DNA replication initiation factor knockdowns that registered >25% overrepresented read-counts, primarily in the S phase category. c As in a but for proteasome component knockdowns that registered >25% overrepresented read-counts, primarily in the G2M category. d As in a but for kinetochore component knockdowns that registered >25% overrepresented read-counts, primarily in the G2M category./p>25% overrepresentation in the S phase pool are components of the eukaryotic replicative helicase, the CMG (Cdc45-MCM-GINS) complex. At the core of this complex is the minichromosome maintenance complex (MCM2-7), a helicase that unwinds the duplex DNA ahead of the moving replication fork68. Identification of CMG complex components suggests that each of these subunits is required for timely progression through S phase./p>25% overrepresentation in the G2M pool. This output is consistent with the view that the T. brucei proteasome is responsible for degrading cell cycle regulators, such as poly-ubiquitinated cyclins, some of which are known to control cell cycle checkpoints in T. brucei. Candidate targets in T. brucei include: CIF1, AUK170, cyclin 6 (CYC6), degradation of which is required for mitosis71; cyclin-like CFB2, required for cytokinesis72; and cyclin 2 (CYC2) or cyclin 3 (CYC3), which have short half-lives and a candidate destruction box motif in the case of CYC373./p>25% overrepresentation in the G2M pool, suggesting that these particular kinetochore components, which all display temporal patterns of phosphorylation from S phase to G2M21, are required for progression through mitosis. Notably, KKT10 is a kinase responsible for phosphorylation of KKT7, which is required for the metaphase to anaphase transition74; as well as for the phosphorylation of KKT1 and KKT2, in turn required for kinetochore assembly75,76. These findings are consistent with the view that kinetochore components control a non-canonical spindle checkpoint in trypanosomes74./p>25% overrepresentation in these pools (Fig. 6a). These include knockdowns for RBP10 and RBP29 enriched in G1; RBP10, in particular, has been characterised in some detail and promotes the bloodstream form state77. ZC3H1178, ZC3H41 and ZC3H2879 knockdowns were enriched in G1, S phase and G2M, respectively, while knockdowns of CFB2, MKT1 or PBP1, all recently linked to variant surface glycoprotein expression control80,81, were enriched in G2M. Indeed, based on the outputs of the current screen, we prioritised these latter three RBPs for follow-up analysis in a separate study; all three were thereby validated as G2M hits80. Thus, the RIT-seq cell cycle screen implicated a number of specific RBPs in post-transcriptional control of cell cycle progression through modulation of mRNA stability and/or translation./p>25% overrepresented read-counts in the G1, S phase or G2M categories are indicated, in purple, green and blue, respectively. The read-mapping profiles and relative read-counts in the other panels show example hits. b As in a but for protein kinase knockdowns, with selected kinases indicated. c As in a but for hypothetical (conserved) protein knockdowns./p>4 C (Fig. 3d), S phase or G2M (Fig. 5d) phenotypes, and now show the RIT-seq profiling data for five additional protein kinase knockdowns that register >25% overrepresentation in the G1, S phase or G2M pools (Fig. 6b). These include knockdowns for CRK7, linked to accumulation in G1; MAPK5, linked to accumulation in S phase and polo-like kinase (PLK) and cdc2-related kinase 3 (CRK3), linked to accumulation in G2M. PLK was previously shown to control cell morphology, furrow ingression and cytokinesis82,83,84, while CRK3 was shown to play a role in G2M progression in bloodstream form T. brucei43,85. Overall correspondence was also excellent with a prior kinome-wide RNAi screen43. For example, eight among nine kinases linked to a mitosis defect in that screen also reported an (21 ± 12%) increase in the G2M pool in the current screen./p>2500 genes. We show data for several hypothetical protein knockdowns above, linked to the enriched >4 C phenotype (Supplementary Fig. 4), and we here identify >300 additional hypothetical protein knockdowns that register >25% overrepresentation in the G1, S phase or G2M pools. RIT-seq profiling data are shown for five examples in Fig. 6c and for several additional examples in Supplementary Fig. 5. Amongst other examples of knockdowns shown in Supplementary Fig. 5, are alternative oxidase86, linked to G1 enrichment; kinesins linked to G2M enrichment, including both chromosomal passenger complex kinesins (KIN-A and KIN-B)26 and KIN-G; CYC625,87, centrin 388 and, finally, both components of the histone chaperone FACT (facilitates chromatin transcription) complex89 Spt16 and Pob3, linked to G2M enrichment. Notably, the FACT complex has been linked to centromere function in human cells90./p>4 C pools (χ2 p = 8.9−9) following knockdown, including kinetochore and chromosomal passenger complex components, respectively. Some specific transcripts required for cell cycle progression may be upregulated prior to peak demand for the encoded protein, and we found evidence to support this view. For example, transcripts upregulated in late G1 or in S phase were enriched amongst those knockdowns linked to accumulation in the G2M pool (χ2 p = 3.3−3 and p = 0.011, respectively); both components of the FACT complex, upregulated in G1, for example (see Supplementary Fig. 5). Similarly, S phase and G2M upregulated transcripts, including those encoding multiple flagellum-associated proteins, were enriched amongst knockdowns linked to accumulation in the >4 C pool (χ2 p = 4.6−18 and p = 2.4−5 respectively)./p>4 C hit in bloodstream-form trypanosomes, we assembled a pair of independent inducible RNAi knockdown strains. Analysis of cell growth revealed a severe loss-of-fitness following knockdown, confirmed by qRT-PCR (Fig. 7c). Flow cytometry then confirmed endoreduplication, with prominent peaks detected representing 8 C and 16 C cells following knockdown (Fig. 7d, left-hand panel), while examination of these cells by microscopy revealed multiple nuclei, indicating endoreduplication with continued mitosis (Fig. 7d, right-hand panel)./p>4 C (~9 × 105 cells) based on their DNA content and collected into 50 ml Falcon tubes (BD Falcon); total sorting time was approx. 4 h. The 2 C, 2–4 C and 4 C sorted samples were then run on a FACS LSR Fortessa flow cytometry analyser for a post-sorting quality check. For the analysis of Tb927.10.970 or Tb927.10.3970 knockdowns, 1 × 107 cells were centrifuged for 10 min at 1000 g, washed in supplemented PBS. Cells were fixed for 10 min in 1% paraformaldehyde in supplemented PBS, washed and stored at 4 °C in supplemented PBS. Cells were pelleted for 10 min at 1000 g and permeabilised at room temperature for 30 min in supplemented PBS plus 0.01% Triton X-100. Cells were washed once in supplemented PBS followed by centrifugation for 10 min at 700 g and then stained in supplemented PBS with 10 μg.ml−1 propidium iodide and 100 μg.ml−1 RNAse A for 1 h at 37 °C. The samples were run on a BD FACSCanto (Becton Dickinson). FlowJo v10.7.1 was used for data analysis and visualisation./p>

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