Dual RNA Sequencing Meta-analysis in Plasmodium Infection Identifies Host-Parasite Interactions

ABSTRACT Dual RNA sequencing (RNA-Seq) is the simultaneous transcriptomic analysis of interacting symbionts, for example, in malaria. Potential cross-species interactions identified by correlated gene expression might highlight interlinked signaling, metabolic, or gene regulatory pathways in addition to physically interacting proteins. Often, malaria studies address one of the interacting organisms—host or parasite—rendering the other “contamination.” Here we perform a meta-analysis using such studies for cross-species expression analysis. We screened experiments for gene expression from host and Plasmodium. Out of 171 studies in Homo sapiens, Macaca mulatta, and Mus musculus, we identified 63 potential studies containing host and parasite data. While 16 studies (1,950 samples) explicitly performed dual RNA-Seq, 47 (1,398 samples) originally focused on one organism. We found 915 experimental replicates from 20 blood studies to be suitable for coexpression analysis and used orthologs for meta-analysis across different host-parasite systems. Centrality metrics from the derived gene expression networks correlated with gene essentiality in the parasites. We found indications of host immune response to elements of the Plasmodium protein degradation system, an antimalarial drug target. We identified well-studied immune responses in the host with our coexpression networks, as our approach recovers known broad processes interlinked between hosts and parasites in addition to individual host and parasite protein associations. The set of core interactions represents commonalities between human malaria and its model systems for prioritization in laboratory experiments. Our approach might also allow insights into the transferability of model systems for different pathways in malaria studies. IMPORTANCE Malaria still causes about 400,000 deaths a year and is one of the most studied infectious diseases. The disease is studied in mice and monkeys as lab models to derive potential therapeutic intervention in human malaria. Interactions between Plasmodium spp. and its hosts are either conserved across different host-parasite systems or idiosyncratic to those systems. Here we use correlation of gene expression from different RNA-Seq studies to infer common host-parasite interactions across human, mouse, and monkey studies. First, we find a set of very conserved interactors, worth further scrutiny in focused laboratory experiments. Second, this work might help assess to which extent experiments and knowledge on different pathways can be transferred from models to humans for potential therapy.

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Publicly available transcriptomes provide the opportunity for dual RNA-Seq meta analysis in Plasmodium infection

10.1101/576116 ◽

2019 ◽

Cited By ~ 1

Author(s):

Parnika Mukherjee ◽

Gaétan Burgio ◽

Emanuel Heitlinger

Keyword(s):

Gene Expression ◽

Species Interactions ◽

Homo Sapiens ◽

Meta Analysis ◽

Model Systems ◽

Rna Seq ◽

Experimental Conditions ◽

Regulatory Pathways ◽

Or Gene ◽

Host Parasite

AbstractDual RNA-Seq is the simultaneous analysis of host and parasite transcriptomes. It can potentially identify host-parasite interactions by correlated gene expression. Co-expression might highlight interlinked signalling, metabolic or gene regulatory pathways in addition to potentially physically interacting proteins. Numerous studies on malaria focus on one organism – either the host or the parasite – and the other is considered contaminant. Here we assess the applicability of a meta-analysis approach for dual RNA-Seq.We screened malaria transcriptome experiments for gene expression data from both Plasmodium and its host. Out of 171 malaria studies in Homo sapiens, Macaca mulatta and Mus musculus, we identified 63 studies with the potential to provide host and parasite data. While 16 studies (1950 total samples) explicitly aimed to generate dual RNA-Seq data, 47 (1398 samples) had an original focus on either the host or the parasite. We show that a total of up to 727 samples from blood and liver studies are suitable for dual RNA-Seq analysis. As a proof-of-principle, we conceive and apply a method for meta-analysis linking host-parasite systems via orthologs. Our approach recovered broad processes known to be interlinked between host and parasites in malaria in addition to individual associations between host and parasite proteins. We suggest these for further experimental investigation.We argue that the multitude of variations in experimental conditions found in the selected studies should help narrow down a conserved core of cross-species interactions. In the future, detailed analyses building on the datasets and concepts conceived here, conserved sets of core interacting pathways and co-regulated genes across study systems might be identified. This might also provide the opportunity to gauge the applicability of model systems for different pathways in malaria studies.

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Host and Parasite Transcriptomic Changes upon Successive Plasmodium falciparum Infections in Early Childhood

mSystems ◽

10.1128/msystems.00116-20 ◽

2020 ◽

Vol 5 (4) ◽

Author(s):

Katie R. Bradwell ◽

Drissa Coulibaly ◽

Abdoulaye K. Koné ◽

Matthew B. Laurens ◽

Ahmadou Dembélé ◽

...

Keyword(s):

Gene Expression ◽

Plasmodium Falciparum ◽

Expression Profiles ◽

Severe Disease ◽

Cell Subset ◽

Gene Expression Profiles ◽

Rna Seq ◽

Blood Samples ◽

Content Type ◽

Host Parasite

ABSTRACT Children are highly susceptible to clinical malaria, and in regions where malaria is endemic, their immune systems must face successive encounters with Plasmodium falciparum parasites before they develop immunity, first against severe disease and later against uncomplicated malaria. Understanding cellular and molecular interactions between host and parasites during an infection could provide insights into the processes underlying this gradual acquisition of immunity, as well as to how parasites adapt to infect hosts that are successively more malaria experienced. Here, we describe methods to analyze the host and parasite gene expression profiles generated simultaneously from blood samples collected from five consecutive symptomatic P. falciparum infections in three Malian children. We show that the data generated enable statistical assessment of the proportions of (i) each white blood cell subset and (ii) the parasite developmental stages, as well as investigations of host-parasite gene coexpression. We also use the sequences generated to analyze allelic variations in transcribed regions and determine the complexity of each infection. While limited by the modest sample size, our analyses suggest that host gene expression profiles primarily clustered by individual, while the parasite gene expression profiles seemed to differentiate early from late infections. Overall, this study provides a solid framework to examine the mechanisms underlying acquisition of immunity to malaria infections using whole-blood transcriptome sequencing (RNA-seq). IMPORTANCE We show that dual RNA-seq from patient blood samples allows characterization of host/parasite interactions during malaria infections and can provide a solid framework to study the acquisition of antimalarial immunity, as well as the adaptations of P. falciparum to malaria-experienced hosts.

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A Family of Viral Satellites Manipulates Invading Virus Gene Expression and Can Affect Cholera Toxin Mobilization

mSystems ◽

10.1128/msystems.00358-20 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Zachary K. Barth ◽

Zoe Netter ◽

Angus Angermeyer ◽

Pooja Bhardwaj ◽

Kimberley D. Seed

Keyword(s):

Gene Expression ◽

Cholera Toxin ◽

Vibrio Cholerae ◽

Rna Sequencing ◽

Expression Patterns ◽

Rna Seq ◽

Time Resolved ◽

Content Type ◽

Domains Of Life ◽

Time Courses

ABSTRACT Many viruses possess temporally unfolding gene expression patterns aimed at subverting host defenses, commandeering host metabolism, and ultimately producing a large number of progeny virions. High-throughput omics tools, such as RNA sequencing (RNA-seq), have dramatically enhanced the resolution of expression patterns during infection. Less studied have been viral satellites, mobile genomes that parasitize viruses. By performing RNA-seq on infection time courses, we have obtained the first time-resolved transcriptomes for bacteriophage satellites during lytic infection. Specifically, we have acquired transcriptomes for the lytic Vibrio cholerae phage ICP1 and all five known variants of ICP1’s parasite, the phage inducible chromosomal island-like elements (PLEs). PLEs rely on ICP1 for both DNA replication and mobilization and abolish production of ICP1 progeny in infected cells. We investigated PLEs’ impact on ICP1 gene expression and found that PLEs did not broadly restrict or reduce ICP1 gene expression. A major exception occurred in ICP1’s capsid morphogenesis operon, which was downregulated by each of the PLE variants. Surprisingly, PLEs were also found to alter the gene expression of CTXΦ, the integrative phage that encodes cholera toxin and is necessary for virulence of toxigenic V. cholerae. One PLE, PLE1, upregulated CTXΦ genes involved in replication and integration and boosted CTXΦ mobility following induction of the SOS response. IMPORTANCE Viral satellites are found in all domains of life and can have profound fitness effects on both the viruses they parasitize and the cells they reside in. In this study, we have acquired the first RNA sequencing (RNA-seq) transcriptomes of viral satellites outside plants, as well as the transcriptome of the phage ICP1, a predominant predator of pandemic Vibrio cholerae. Capsid downregulation, previously observed in an unrelated phage satellite, is conserved among phage inducible chromosomal island-like elements (PLEs), suggesting that viral satellites are under strong selective pressure to reduce the capsid expression of their larger host viruses. Despite conserved manipulation of capsid expression, PLEs exhibit divergent effects on CTXΦ transcription and mobility. Our results demonstrate that PLEs can influence both their hosts’ resistance to phage and the mobility of virulence-encoding elements, suggesting that PLEs can play a substantial role in shaping Vibrio cholerae evolution.

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Genotype-free individual genome reconstruction of Multiparental Population Models by RNA sequencing data

10.1101/2020.10.11.335323 ◽

2020 ◽

Author(s):

Kwangbom Choi ◽

Hao He ◽

Daniel M. Gatti ◽

Vivek M. Philip ◽

Narayanan Raghupathy ◽

...

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Gene Expression Regulation ◽

Agricultural Research ◽

Model Systems ◽

Specific Gene ◽

Rna Seq ◽

Sequencing Data ◽

Individual Genome ◽

Genome Reconstruction

AbstractMulti-parent populations (MPPs), genetically segregating model systems derived from two or more inbred founder strains, are widely used in biomedical and agricultural research. Gene expression profiling by direct RNA sequencing (RNA-Seq) is commonly applied to MPPs to investigate gene expression regulation and to identify candidate genes. In genetically diverse populations, including most MPPs, quantification of gene expression is improved when the RNA-Seq reads are aligned to individualized transcriptomes that incorporate known polymorphic loci. However, the process of constructing and analyzing individual genomes can be computationally demanding and error prone. We propose a new approach, genome reconstruction by RNA-Seq (GBRS), that relies on simultaneous alignment of RNA-Seq reads to the founder strain transcriptomes. GBRS can reconstruct the diploid genome of each individual and quantify both total and allele-specific gene expression. We demonstrate that GBRS performs as well as methods that rely on high-density genotyping arrays to reconstruct the founder haplotype mosaic of MPP individuals. Using GBRS in addition to other genotyping methods provides quality control for detecting sample mix-ups and improves power to detect expression quantitative trait loci. GBRS software is freely available at https://github.com/churchill-lab/gbrs.

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Spatial expression pattern of serine proteases in the blood fluke Schistosoma mansoni determined by fluorescence RNA in situ hybridization

Parasites & Vectors ◽

10.1186/s13071-021-04773-8 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Lenka Ulrychová ◽

Pavel Ostašov ◽

Marta Chanová ◽

Michael Mareš ◽

Martin Horn ◽

...

Keyword(s):

In Situ Hybridization ◽

Schistosoma Mansoni ◽

Rna Sequencing ◽

Serine Proteases ◽

Expression Patterns ◽

High Sensitivity ◽

Host Parasite Interactions ◽

Highly Sensitive ◽

Host Parasite

Abstract Background The blood flukes of genus Schistosoma are the causative agent of schistosomiasis, a parasitic disease that infects more than 200 million people worldwide. Proteases of schistosomes are involved in critical steps of host–parasite interactions and are promising therapeutic targets. We recently identified and characterized a group of S1 family Schistosoma mansoni serine proteases, including SmSP1 to SmSP5. Expression levels of some SmSPs in S. mansoni are low, and by standard genome sequencing technologies they are marginally detectable at the method threshold levels. Here, we report their spatial gene expression patterns in adult S. mansoni by the high-sensitivity localization assay. Methodology Highly sensitive fluorescence in situ RNA hybridization (FISH) was modified and used for the localization of mRNAs encoding individual SmSP proteases (including low-expressed SmSPs) in tissues of adult worms. High sensitivity was obtained due to specifically prepared tissue and probes in combination with the employment of a signal amplification approach. The assay method was validated by detecting the expression patterns of a set of relevant reference genes including SmCB1, SmPOP, SmTSP-2, and Sm29 with localization formerly determined by other techniques. Results FISH analysis revealed interesting expression patterns of SmSPs distributed in multiple tissues of S. mansoni adults. The expression patterns of individual SmSPs were distinct but in part overlapping and were consistent with existing transcriptome sequencing data. The exception were genes with significantly low expression, which were also localized in tissues where they had not previously been detected by RNA sequencing methods. In general, SmSPs were found in various tissues including reproductive organs, parenchymal cells, esophagus, and the tegumental surface. Conclusions The FISH-based assay provided spatial information about the expression of five SmSPs in adult S. mansoni females and males. This highly sensitive method allowed visualization of low-abundantly expressed genes that are below the detection limits of standard in situ hybridization or by RNA sequencing. Thus, this technical approach turned out to be suitable for sensitive localization studies and may also be applicable for other trematodes. The results suggest that SmSPs may play roles in diverse processes of the parasite. Certain SmSPs expressed at the surface may be involved in host–parasite interactions. Graphic abstract

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HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽

10.3390/v13020244 ◽

2021 ◽

Vol 13 (2) ◽

pp. 244 ◽

Cited By ~ 1

Author(s):

Antonio Victor Campos Coelho ◽

Rossella Gratton ◽

João Paulo Britto de Melo ◽

José Leandro Andrade-Santos ◽

Rafael Lima Guimarães ◽

...

Keyword(s):

Gene Expression ◽

T Cells ◽

Differentially Expressed Genes ◽

Cd4 T Cells ◽

Expression Profiles ◽

Meta Analysis ◽

Differentially Expressed ◽

Rna Seq ◽

Infected Cells ◽

Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

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Multi-species transcriptome meta-analysis of the response to retinoic acid in vertebrates and comparative analysis of the effects of retinol and retinoic acid on gene expression in LMH cells

BMC Genomics ◽

10.1186/s12864-021-07451-2 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Clemens Falker-Gieske ◽

Andrea Mott ◽

Sören Franzenburg ◽

Jens Tetens

Keyword(s):

Gene Expression ◽

Retinoic Acid ◽

Cellular Response ◽

Homo Sapiens ◽

Meta Analysis ◽

Early Response ◽

Rna Seq ◽

Transcriptomic Response ◽

Time Points ◽

Lmh Cells

Abstract Background Retinol (RO) and its active metabolite retinoic acid (RA) are major regulators of gene expression in vertebrates and influence various processes like organ development, cell differentiation, and immune response. To characterize a general transcriptomic response to RA-exposure in vertebrates, independent of species- and tissue-specific effects, four publicly available RNA-Seq datasets from Homo sapiens, Mus musculus, and Xenopus laevis were analyzed. To increase species and cell-type diversity we generated RNA-seq data with chicken hepatocellular carcinoma (LMH) cells. Additionally, we compared the response of LMH cells to RA and RO at different time points. Results By conducting a transcriptome meta-analysis, we identified three retinoic acid response core clusters (RARCCs) consisting of 27 interacting proteins, seven of which have not been associated with retinoids yet. Comparison of the transcriptional response of LMH cells to RO and RA exposure at different time points led to the identification of non-coding RNAs (ncRNAs) that are only differentially expressed (DE) during the early response. Conclusions We propose that these RARCCs stand on top of a common regulatory RA hierarchy among vertebrates. Based on the protein sets included in these clusters we were able to identify an RA-response cluster, a control center type cluster, and a cluster that directs cell proliferation. Concerning the comparison of the cellular response to RA and RO we conclude that ncRNAs play an underestimated role in retinoid-mediated gene regulation.

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Transcriptome of the parasitic flatworm Schistosoma mansoni during intra-mammalian development

10.1101/757633 ◽

2019 ◽

Cited By ~ 3

Author(s):

Arporn Wangwiwatsin ◽

Anna V. Protasio ◽

Shona Wilson ◽

Christian Owusu ◽

Nancy E. Holroyd ◽

...

Keyword(s):

Gene Expression ◽

Schistosoma Mansoni ◽

Chronic Infection ◽

Egg Laying ◽

Mammalian Host ◽

Expression Data ◽

Mammalian Development ◽

Host Parasite Interactions ◽

Parasitic Flatworm ◽

Host Parasite

AbstractSchistosomes are parasitic blood flukes that survive for many years within the mammalian host vasculature. How the parasites establish a chronic infection in the hostile bloodstream environment, whilst evading the host immune response is poorly understood. The parasite develops morphologically and grows as it migrates to its preferred vascular niche, avoiding or repairing damage from the host immune system. In this study, we investigated temporal changes in gene expression during the intra-mammalian development of Schistosoma mansoni. RNA-seq data were analysed from parasites developing in the lung through to egg-laying mature adult worms, providing a comprehensive picture of in vivo intra-mammalian development. Remarkably, genes involved in signalling pathways, developmental control, and adaptation to oxidative stress were up-regulated in the lung stage. The data also suggested a potential role in immune evasion for a previously uncharacterised gene. This study not only provides a large and comprehensive data resource for the research community, but also reveals new directions for further characterising host–parasite interactions that could ultimately lead to new control strategies for this neglected tropical disease pathogen.Author SummaryThe life cycle of the parasitic flatworm Schistosoma mansoni is split between snail and mammalian (often human) hosts. An infection can last for more than 10 years, during which time the parasite physically interacts with its mammalian host as it moves through the bloodstream, travelling through the lungs and liver, to eventually establish a chronic infection in the blood vessels around the host gut. Throughout this complex journey, the parasite develops from a relatively simple larval form into a more complex, sexually reproducing adult. To understand the molecular basis of parasite interactions with the host during this complex journey we have produced genome-wide expression data from developing parasites. The parasites were collected from experimentally-infected mice over its developmental time-course from the poorly studied lung stage, to the fully mature egg-laying adult worm. The data highlight many genes involved in processes known to be associated with key stages of the infection. In addition, the gene expression data provide a unique view of interactions between the parasite and the immune system in the lung, including novel players in host-parasite interactions. A detailed understanding of these processes may provide new opportunities to design intervention strategies, particularly those focussed on the early stages of the infection that are not targeted by current chemotherapy.

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Importance of experimental information (metadata) for archived sequence data: case of specific gene bias due to lag time between sample harvest and RNA protection in RNA sequencing

PeerJ ◽

10.7717/peerj.11875 ◽

2021 ◽

Vol 9 ◽

pp. e11875

Author(s):

Tomoko Matsuda

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Time Course ◽

Sequence Data ◽

Specific Gene ◽

Time Interval ◽

Short Time Interval ◽

Rna Seq ◽

Lysis Buffer ◽

Rna Protection

Large volumes of high-throughput sequencing data have been submitted to the Sequencing Read Archive (SRA). The lack of experimental metadata associated with the data makes reuse and understanding data quality very difficult. In the case of RNA sequencing (RNA-Seq), which reveals the presence and quantity of RNA in a biological sample at any moment, it is necessary to consider that gene expression responds over a short time interval (several seconds to a few minutes) in many organisms. Therefore, to isolate RNA that accurately reflects the transcriptome at the point of harvest, raw biological samples should be processed by freezing in liquid nitrogen, immersing in RNA stabilization reagent or lysing and homogenizing in RNA lysis buffer containing guanidine thiocyanate as soon as possible. As the number of samples handled simultaneously increases, the time until the RNA is protected can increase. Here, to evaluate the effect of different lag times in RNA protection on RNA-Seq data, we harvested CHO-S cells after 3, 5, 6, and 7 days of cultivation, added RNA lysis buffer in a time course of 15, 30, 45, and 60 min after harvest, and conducted RNA-Seq. These RNA samples showed high RNA integrity number (RIN) values indicating non-degraded RNA, and sequence data from libraries prepared with these RNA samples was of high quality according to FastQC. We observed that, at the same cultivation day, global trends of gene expression were similar across the time course of addition of RNA lysis buffer; however, the expression of some genes was significantly different between the time-course samples of the same cultivation day; most of these differentially expressed genes were related to apoptosis. We conclude that the time lag between sample harvest and RNA protection influences gene expression of specific genes. It is, therefore, necessary to know not only RIN values of RNA and the quality of the sequence data but also how the experiment was performed when acquiring RNA-Seq data from the database.

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Elucidation of Regulatory Modes for Five Two-Component Systems in Escherichia coli Reveals Novel Relationships

mSystems ◽

10.1128/msystems.00980-20 ◽

2020 ◽

Vol 5 (6) ◽

Author(s):

Kumari Sonal Choudhary ◽

Julia A. Kleinmanns ◽

Katherine Decker ◽

Anand V. Sastry ◽

Ye Gao ◽

...

Keyword(s):

Gene Expression ◽

Escherichia Coli ◽

Target Gene ◽

Target Genes ◽

Rna Seq ◽

Content Type ◽

E Coli ◽

Component Systems ◽

Two Component ◽

Two Component Systems

ABSTRACT Escherichia coli uses two-component systems (TCSs) to respond to environmental signals. TCSs affect gene expression and are parts of E. coli’s global transcriptional regulatory network (TRN). Here, we identified the regulons of five TCSs in E. coli MG1655: BaeSR and CpxAR, which were stimulated by ethanol stress; KdpDE and PhoRB, induced by limiting potassium and phosphate, respectively; and ZraSR, stimulated by zinc. We analyzed RNA-seq data using independent component analysis (ICA). ChIP-exo data were used to validate condition-specific target gene binding sites. Based on these data, we do the following: (i) identify the target genes for each TCS; (ii) show how the target genes are transcribed in response to stimulus; and (iii) reveal novel relationships between TCSs, which indicate noncognate inducers for various response regulators, such as BaeR to iron starvation, CpxR to phosphate limitation, and PhoB and ZraR to cell envelope stress. Our understanding of the TRN in E. coli is thus notably expanded. IMPORTANCE E. coli is a common commensal microbe found in the human gut microenvironment; however, some strains cause diseases like diarrhea, urinary tract infections, and meningitis. E. coli’s two-component systems (TCSs) modulate target gene expression, especially related to virulence, pathogenesis, and antimicrobial peptides, in response to environmental stimuli. Thus, it is of utmost importance to understand the transcriptional regulation of TCSs to infer bacterial environmental adaptation and disease pathogenicity. Utilizing a combinatorial approach integrating RNA sequencing (RNA-seq), independent component analysis, chromatin immunoprecipitation coupled with exonuclease treatment (ChIP-exo), and data mining, we suggest five different modes of TCS transcriptional regulation. Our data further highlight noncognate inducers of TCSs, which emphasizes the cross-regulatory nature of TCSs in E. coli and suggests that TCSs may have a role beyond their cognate functionalities. In summary, these results can lead to an understanding of the metabolic capabilities of bacteria and correctly predict complex phenotype under diverse conditions, especially when further incorporated with genome-scale metabolic models.

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