A rising tide of parasite transcriptomics propels pathogen biology

Quotation: Duraisingh MT, Gubbels M-J, Zarringhalam Okay (2023) A rising tide of parasite transcriptomics propels pathogen biology. PLoS Biol 21(1):
e3001997.

https://doi.org/10.1371/journal.pbio.3001997

Revealed: January 25, 2023

Copyright: © 2023 Duraisingh et al. That is an open entry article distributed beneath the phrases of the Inventive Commons Attribution License, which allows unrestricted use, distribution, and copy in any medium, supplied the unique writer and supply are credited.

Funding: This work was supported by the Nationwide Institutes of Well being (NIH R01AI167570 to MG, KZ and MTD). The funders had no position in research design, knowledge assortment and evaluation, resolution to publish, or preparation of the manuscript.

Competing pursuits: The authors have declared that no competing pursuits exist.

Abbreviations:
AI,
synthetic intelligence; IDC,
intraerythrocytic developmental cycle; qRT-PCR,
quantitative reverse transcription PCR; RNA-seq,
RNA sequencing

This text is a part of the PLOS Biology twentieth Anniversary Assortment.

The appearance of microarrays within the late Nineties heralded the age of transcriptomics in mannequin techniques. Twenty years in the past, in a landmark paper printed within the first challenge of PLOS Biology [1], Bozdech, Llinas, and colleagues described the primary acquisition of the transcriptome of the intraerythrocytic developmental cycle (IDC) of the apicomplexan malaria parasite Plasmodium falciparum, which nonetheless infects over 250 million individuals and kills about 500,000 individuals every year. This work was monumental, significantly contemplating that the P. falciparum genome had solely been printed a 12 months earlier in 2002 [2]. The immediate public availability of the sequences allowed the expedient design of 70-bp oligonucleotide arrays corresponding to each gene within the P. falciparum genome [3]. The investigators leveraged the flexibility to tradition this parasite at scale to organize RNA at completely different time factors inside the IDC for quantitative evaluation on an oligonucleotide-based microarray. This strategy resulted within the first visualization of the once-a-cycle just-in-time transcription of nearly all of genes inside the malaria parasite, resembling the cascades of a viral-like life cycle. Strikingly, it supplied a list of all of the expressed genes within the IDC at a genomic degree, a quantum leap in scale past the normal strategies of northern blotting and quantitative reverse transcription PCR (qRT-PCR) (Fig 1). The quantitative knowledge obtained within the early days had been initially acquired with a point of skepticism by the sphere however have clearly stood the check of time, and this paper [1] is now some of the extremely cited within the area (Google Scholar: 1,844 citations on the time of this publication).

Fig 1. The evolution of parasite transcriptomics.

The appearance of the expression microarray was a transformative occasion that for the primary time revealed dynamic, genome-wide expression modifications. Over time, within the postgenomic period, this has turn into extra refined in spatiotemporal decision. The following wave of techniques biology requires new computational instruments which might be anticipated to disclose new elements of parasite biology for translation. Tailored from [1]. AI, synthetic intelligence; EST, expressed sequence tag; ML, machine studying; qRT-PCR, quantitative reverse transcription PCR; ribo-seq, ribosome sequencing; RNA-Seq, RNA sequencing; SAGE, Serial Evaluation of Gene Expression; scRNA-seq, single-cell RNA sequencing; SNV, single-nucleotide variation; UMAP, Uniform Manifold Approximation and Projection.

https://doi.org/10.1371/journal.pbio.3001997.g001

The oligonucleotide arrays had been significantly helpful for evaluating completely different transcriptomes. The printing of the arrays was cheap, making them out there for quite a few functions. Along with the wonderful decision of the completely different phases of the IDC, the arrays had been used to evaluate perturbations to in vitro cultures, together with the addition of medication and inhibitors to evaluate molecular mechanisms [4], and the purposeful evaluation of genetic mutants to determine particular transcriptional applications [5]. Transcriptomics had been used to evaluate expression-level polymorphisms between strains, ensuing within the identification of a “variantome,” related to virulence gene expression [6]. Lastly, a whole bunch of parasites from endemic populations had been interrogated, revealing transcriptional applications related to distinct transmission methods [7]. In a parallel strategy, the Affymetrix platform was equally used for the evaluation of the P. falciparum transcriptome over the parasite developmental cycle [8], revealing expression of particular genes on the beforehand obscure insect and liver phases.

Transcriptomics, trailblazed by these research in P. falciparum, has remodeled the sphere of parasitology. The expertise has been democratically utilized to quite a few parasites (different Plasmodium spp. and different parasites of medical significance), enabling comparative research which have revealed species-specific improvements. Basic challenges have included the necessity for synchronization, the presence of transcriptionally lively host cells, and the brief length of the cell cycle (a serious problem for the evolutionarily associated apicomplexan Toxoplasma gondii; [9]), in addition to the supply of sufficient materials at completely different phases of the usually complicated life cycles of parasites. However, transcriptomes are actually out there for all the most important pathogens of people, facilitating quite a few research geared toward understanding the biology of those pathogens and informing translation for therapeutic growth.

Transcriptomics itself advanced from microarrays to using next-generation RNA sequencing (RNA-Seq) applied sciences that allowed for the simultaneous quantitation and visualization of coding and noncoding mRNAs in bulk populations of parasites (Fig 1). Most just lately, the arrival of single-cell approaches, reminiscent of scRNA-Seq, scATAC-Seq, and perturb-Seq, are more and more tailored and utilized for parasitology research, pushing this area additional into the area of “data-intensive sciences.” Certainly, a number of current research have generated atlases of scRNA-Seq knowledge for a various vary of parasites and life cycle phases, together with for malaria parasites [10]. These invaluable knowledge assets, mixed with computational fashions, present highly effective instruments to check gene expression and regulatory occasions at single-cell decision.

Vital to the interpretation of the transcriptomic knowledge has been its integration with different ‘omic knowledge units. For one, the acquisition of the proteomes by way of the IDC for P. falciparum clearly demonstrated an absence of concordance between transcripts and proteins [11]. A lot effort is presently being devoted to the outline and understanding of posttranscriptional gene regulation. The acquisition of multiomic knowledge at a number of ranges will feed into the arrival of techniques biology approaches to disclose mechanisms in complicated host–parasite techniques. Of explicit observe is the VeuPathDB database, an unimaginable group useful resource that’s the residence of genomic knowledge and evaluation instruments for eukaryotic pathogens and their vectors.

We anticipate a future the place the prices of transcriptomic measurements will go down dramatically and accessibility will enhance, putting it on the coronary heart of the evaluation of parasite biology. Superior algorithms and software program packages have been developed for the evaluation, integration, and interpretation of multiomics and single-cell knowledge. Nonetheless, many challenges stay unresolved. As an example, computational fashions are primarily developed for mammalian cells, and a number of other challenges restrict their utility for the evaluation of parasite knowledge. New approaches and instruments from statistics, pc science, and knowledge engineering are wanted to explicitly mannequin and combine the distinctive options of parasite biology. As well as, in contrast to mannequin organisms, the place in depth data is on the market on regulatory networks, metabolic pathways, and posttranslational modifiers, such assets for parasites are restricted. Most genes in parasites are presently functionally uncharacterized, and the parasite genomes are poorly annotated. These limitations hamper the event of holistic techniques biology approaches to check mobile processes in parasites. Nonetheless, new datasets on regulatory interactions are being generated at a speedy tempo, reminiscent of ChIP-seq [12], enabling the mixing of a number of sources of knowledge and community biology approaches for parasitology functions.