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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 1,621 records · Page 90Linked to original sources

bioRxiv2018

A simple microbiome in esophagus and gills of the European common cuttlefish, Sepia officinalis

The European common cuttlefish, Sepia officinalis, is used extensively in biological and biomedical research yet its microbiome remains poorly characterized. We analyzed the microbiota of the digestive tract, gills, and skin in mariculture-raised S. officinalis using a combination of 16s rRNA amplicon sequencing and fluorescence spectral imaging. Sequencing revealed a highly simplified microbiota consisting largely of two single bacterial amplicon sequence variants (ASVs) of Vibrionaceae and Piscirickettsiaceae. The esophagus was dominated by a single ASV of the genus Vibrio. Imaging revealed a striking organization of bacteria distributed in a discrete layer that lines the esophagus. Imaging with specific probes confirmed the identity of these bacteria as Vibrionaceae. This Vibrio was also abundant in the microbiota of the stomach, cecum, and intestine, but occurred at lower density and in the lumen rather than in a discrete layer; it was present in only trace proportions in tank water and in the microbiome of shrimp that were used as feed for the cuttlefish. These Vibrio were resilient to treatment of animals with the commonly-used antibiotic, enrofloxacin. The gills were colonized by a single ASV in the family Piscirickettsiaceae, which imaging visualized as small clusters of cells. We conclude that bacteria belonging to the Gammaproteobacteria, especially Vibrionaceae, are the major symbionts of the cuttlefish Sepia officinalis cultured from eggs in captivity, and that the esophagus and gills are major colonization sites.\n\nIMPORTANCEMicrobes can play critical roles in the physiology of their animal hosts, as evidenced in cephalopods by the role of Vibrio (Aliivibrio) fischeri in the light organ of the bobtail squid and the role of Alpha- and Gammaproteobacteria in the reproductive system and egg defense in a variety of cephalopods. We sampled the cuttlefish microbiome throughout the digestive tract, gills, and skin and found dense colonization of an unexpected site, the esophagus, by a microbe of the genus Vibrio, as well as colonization of gills by Piscirickettsiaceae. We found these associations to be resilient to the treatment of animals with a common antibiotic, enrofloxacin. This finding expands the range of organisms and body sites known to be associated with Vibrio and is of potential significance for understanding host-symbiont associations as well as for understanding and maintaining the health of cephalopods in mariculture.

microbiology↗

bioRxiv2018

Streptococcus agalactiae induces placental macrophages to release extracellular traps loaded with tissue remodeling enzymes via an oxidative-burst-dependent mechanism

Streptococcus agalactiae, or Group B Streptococcus (GBS), is a common perinatal pathogen. GBS colonization of the vaginal mucosa during pregnancy is a risk factor for invasive infection of the fetal membranes (chorioamnionitis) and its consequences such as membrane rupture, preterm labor, stillbirth, and neonatal sepsis. Placental macrophages, or Hofbauer cells, are fetally-derived macrophages present within placental and fetal membrane tissues that perform vital functions for fetal and placental development, including supporting angiogenesis, tissue remodeling, and regulation of maternal-fetal tolerance. Although placental macrophages, as tissue-resident innate phagocytes, are likely to engage invasive bacteria such as GBS, there is limited information regarding how these cells respond to bacterial infection. Here, we demonstrate in vitro that placental macrophages release macrophage extracellular traps (METs) in response to bacterial infection. Placental macrophage METs contain proteins including histones, myeloperoxidase, and neutrophil elastase similar to neutrophil extracellular traps and are capable of killing GBS cells. MET release from these cells occurs by a process that depends on the production of reactive oxygen species. Placental macrophage METs also contain matrix metalloproteases that are released in response to GBS and could contribute to fetal membrane weakening during infection. MET structures were identified within human fetal membrane tissues infected ex vivo, suggesting that placental macrophages release METs in response to bacterial infection during chorioamnionitis.\n\nImportanceStreptococcus agalactiae, also known as Group B Streptococcus (GBS), is a common pathogen during pregnancy where infection can result in chorioamnionitis, preterm premature rupture of membranes (PPROM), preterm labor, stillbirth, and neonatal sepsis. Mechanisms by which GBS infection results in adverse pregnancy outcomes are still incompletely understood. This study evaluated interactions between GBS and placental macrophages. The data demonstrate that in response to infection, placental macrophages release extracellular traps capable of killing GBS. Additionally, this work establishes that proteins associated with extracellular trap fibers include several matrix metalloproteinases that have been associated with chorioamnionitis. In the context of pregnancy, placental macrophage responses to bacterial infection might have beneficial and adverse consequences, including protective effects against bacterial invasion but also releasing important mediators of membrane breakdown that could contribute to membrane rupture or preterm labor.

microbiology↗

bioRxiv2018

The key parameters that govern translation efficiency

Translation of mRNA into protein is a fundamental yet complex biological process with multiple factors that can potentially affect its efficiency. In particular, different genes can have quite different initiation rates, while site-specific elongation rates can vary substantially along a given transcript. Here, we analyze a stochastic model of translation dynamics to identify the key parameters that govern the overall rate of protein synthesis and the efficiency of ribosome usage. The mathematical model we study is an interacting particle system that generalizes the Totally Asymmetric Simple Exclusion Process (TASEP), where particles correspond to ribosomes. While the TASEP and its variants have been studied for the past several decades through simulations and mean field approximations, a general analytic solution has remained challenging to obtain. By analyzing the so-called hydrodynamic limit, we here obtain exact closed-form expressions for stationary currents and particle densities that agree well with Monte Carlo simulations. In addition, we provide a complete characterization of phase transitions in the system. Surprisingly, phase boundaries depend on only four parameters: the particle size, and the first, last and minimum particle jump rates. Relating these theoretical results to translation, we formulate four design principles that detail how to tune these parameters to optimize translation efficiency in terms of protein production rate and resource usage. We then analyze ribosome profiling data of S. cerevisiae and demonstrate that its translation system is generally efficient, consistent with the design principles we found. We discuss implications of our findings on evolutionary constraints and codon usage bias.

genomics↗

bioRxiv2018

Dynamic load balancing enables large-scale flux variability analysis

Genome-scale metabolic models (GSMMs) of living organisms are used in a wide variety of applications pertaining to health and bioengineering. They are formulated as linear programs (LP) that are often under-determined. Flux Variability Analysis (FVA) characterizes the alternate optimal solution (AOS) space enabling thereby the assessment of the robustness of the solution. fastFVA (FFVA), the C implementation of MATLAB FVA, allowed to gain substantial speed up, although, the parallelism was managed through MATLAB. Here veryfastFVA (VFFVA) is presented, which is a pure C implementation of FVA, that relies on lower level management of parallelism through a hybrid MPI/OpenMP. The flexibility of VFFVA allowed to gain a threefold speedup factor and to decrease memory usage 14 fold in comparison to FFVA. Finally, VFFVA allows processing a higher number of GSMMs in faster times accelerating thereby biomedical modeling and simulation. VFFVA is available online at https://github.com/marouenbg/VFFVA.

bioinformatics↗

bioRxiv2018

Light induced synaptic vesicle autophagy

The regulated turnover of synaptic vesicle (SV) proteins is thought to involve the ubiquitin dependent tagging and degradation through endo-lysosomal and autophagy pathways. Yet, it remains unclear which of these pathways are used, when they become activated and whether SVs are cleared en-mass together with SV proteins or whether both are degraded selectively. Equally puzzling is how quickly these systems can be activated and whether they function in real time to support synaptic health. To address these questions, we have developed an imaging based system that simultaneously tags presynaptic proteins while monitoring autophagy. Moreover, by tagging SV proteins with a light activated reactive oxygen species (ROS) generator, Supernova, it was possible to temporally control the damage to specific SV proteins and assess their consequence to autophagy mediated clearance mechanisms and synaptic function. Our results show that, in mouse hippocampal neurons, presynaptic autophagy can be induced in as little as 5-10 minutes and eliminates primarily the damaged protein rather than the SV en-mass. Importantly, we also find that autophagy is essential for synaptic function, as light-induced damage to e.g. Synaptophysin only compromises synaptic function when autophagy is simultaneously blocked. These data support the concept that presynaptic boutons have a robust highly regulated clearance system to maintain not only synapse integrity, but also synaptic function.

neuroscience↗

bioRxiv2018

Minimal phenotyping yields GWAS hits of low specificity for major depression

Minimal phenotyping refers to the reliance on the use of a small number of self-report items for disease case identification. This strategy has been applied to genome-wide association studies (GWAS) of major depressive disorder (MDD). Here we report that the genotype derived heritability (h2SNP) of depression defined by minimal phenotyping (14%, SE = 0.8%) is lower than strictly defined MDD (26%, SE = 2.2%). This cannot be explained by differences in prevalence between definitions or including cases of lower liability to MDD in minimal phenotyping definitions of depression, but can be explained by misdiagnosis of those without depression or with related conditions as cases of depression. Depression defined by minimal phenotyping is as genetically correlated with strictly defined MDD (rG = 0.81, SE = 0.03) as it is with the personality trait neuroticism (rG = 0.84, SE = 0.05), a trait not defined by the cardinal symptoms of depression. While they both show similar shared genetic liability with neuroticism, a greater proportion of the genome contributes to the minimal phenotyping definitions of depression (80.2%, SE = 0.6%) than to strictly defined MDD (65.8%, SE = 0.6%). We find that GWAS loci identified in minimal phenotyping definitions of depression are not specific to MDD: they also predispose to other psychiatric conditions. Finally, while highly predictive polygenic risk scores can be generated from minimal phenotyping definitions of MDD, the predictive power can be explained entirely by the sample size used to generate the polygenic risk score, rather than specificity for MDD. Our results reveal that genetic analysis of minimal phenotyping definitions of depression identifies non-specific genetic factors shared between MDD and other psychiatric conditions. Reliance on results from minimal phenotyping for MDD may thus bias views of the genetic architecture of MDD and may impede our ability to identify pathways specific to MDD.

genetics↗

bioRxiv2018

Evidence that poor HAART adherence has a great impact on HIV/AIDS treatment failure more than severity of illness and opportunity of infection in Ethiopia: Systematic review and meta-analysis

BackgroundThe pooled burden of HIV treatment failure and its associated factors in Ethiopian context is required to provide evidence towards renewed ambitious future goal.\n\nMethodsPubMed, Web of Science, Scopus, Google Scholar, and Ethiopian Universities (University of Gondar and Addis Ababa University) online repository library were used to get the research articles. I-squared statistics was used to see heterogeneity. Publication bias was checked by Eggers regression test. A meta-analysis using the DerSimonian-Laird random-effects model was employed to estimate the overall prevalence of treatment failure. Subgroup analyses based on the geographical location of the study, age of study population, type of treatment failure, and study design were conducted to see variation in outcomes. The sensitivity analysis was also employed to see whether an outlier result found in the included studies.\n\nResultsOverall HIV treatment failure found to be 15.9% (95% CI: 11.6%-20.1%). HIV treatment failure was 10.2% (6.9%-13.6%) using immunological definition, 5.6% (95% CI: 2.9%-8.3%) using virological definition, and 6.3% (4.6%-8.0%) using clinical definition. Poor HAART adherence (AOR= 8.5; 95% CI: 4.1-12.8), severity of illness (as measured by WHO clinical stage III/IV (AOR=1.9; 95% CI: 1.3-2.6), and presence of opportunistic infections (AOR=1.8; 95% CI: 1.2-2.4) were significantly associated with HIV treatment failure.\n\nConclusionsHIV treatment failure in Ethiopia found to be high and differed by adherence level, severity of illness, and presence of opportunistic infection. HIV intervention programs, such as behavioral intervention is required to sustain HIV treatment adherence and improve treatment success as a result.\n\nProtocol RegistrationIt has been registered in the PROSPERO database (CRD42018100254).

epidemiology↗

bioRxiv2018

Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data

Tumors are made of evolving and heterogeneous populations of cells which arise from successive appearance and expansion of subclonal populations, following acquisition of mutations conferring them a selective advantage. Those subclonal populations can be sensitive or resistant to different treatments, and provide information about tumor aetiology and future evolution. Hence, it is important to be able to assess the level of heterogeneity of tumors with high reliability for clinical applications.\n\nIn the past few years, a large number of methods have been proposed to estimate intra-tumor heterogeneity from whole exome sequencing (WES) data, but the accuracy and robustness of these methods on real data remains elusive. Here we systematically apply and compare 6 computational methods to estimate tumor heterogeneity on 1,697 WES samples from the cancer genome atlas (TCGA) covering 3 cancer types (breast invasive carcinoma, bladder urothelial carcinoma, and head and neck squamous cell carcinoma), and two distinct input mutation sets. We observe significant differences between the estimates produced by different methods, and identify several likely confounding factors in heterogeneity assessment for the different methods. We further show that the prognostic value of tumor heterogeneity for survival prediction is limited in those datasets, and find no evidence that it improves over prognosis based on other clinical variables.\n\nIn conclusion, heterogeneity inference from WES data on a single sample, and its use in cancer prognosis, should be considered with caution. Other approaches to assess intra-tumoral heterogeneity such as those based on multiple samples may be preferable for clinical applications.

bioinformatics↗

bioRxiv2018

The detection of novel and resident marine non-indigenous species using environmental DNA metabarcoding of seawater and sediment

Environmental DNA (eDNA) surveys are increasingly being used for biodiversity monitoring, principally because they are sensitive and can provide high resolution community composition data. Despite considerable progress in recent years, eDNA studies examining how different environmental sample types can affect species detectability remain rare. Comparisons of environmental samples are especially important for providing best practice guidance on early detection and subsequent mitigation of non-indigenous species. Here we used eDNA metabarcoding of COI (cytochrome c oxidase subunit I) and 18S (nuclear small subunit ribosomal DNA) genes to compare community composition between sediment and water samples in artificial coastal sites across the United Kingdom. We first detected markedly different communities and a consistently greater number of distinct operational taxonomic units in sediment compared to water. We then compared our eDNA datasets with previously published rapid assessment biodiversity surveys and found excellent concordance among the different survey techniques. Finally, our eDNA surveys detected many non-indigenous species, including several newly introduced species, highlighting the utility of eDNA metabarcoding for both early detection and temporal / spatial monitoring of non-indigenous species. We conclude that careful consideration on environmental sample type is needed when conducting eDNA surveys, especially for studies assessing community change.

molecular biology↗

bioRxiv2018

Evidence for bias of genetic ancestry in resting state functional MRI

Resting state functional magnetic resonance imaging (rs-fMRI) is a popular imaging modality for mapping the functional connectivity of the brain. Rs-fMRI is, just like other neuroimaging modalities, subject to a series of technical and subject level biases that change the inferred connectivity pattern. In this work we predicted genetic ancestry from rs-fMRI connectivity data at very high performance (area under the ROC curve of 0.93). Thereby, we demonstrated that genetic ancestry is encoded in the functional connectivity pattern of the brain at rest. Consequently, genetic ancestry constitutes a bias that should be accounted for in the analysis of rs-fMRI data.

neuroscience↗

bioRxiv2018

Decreased kinesin-1 mitigates NMDA-induced exicitotoxicity and ischemia-evoked neurodegeneration

N-methyl-D-aspartate receptor (NMDAR) is highly compartmentalized in neurons and the dysfunction has been implicated in various neuropsychiatric and neurodegenerative disorders. Recent failure to exploit NMDAR antagonization as a potential therapeutic target has driven the need to identify molecular mechanisms that regulate NMDAR compartmentalization. Here, we report that neural activity-dependent reduction of Kif5b, the heavy chain of kinesin-1, protected neurons against NMDA-induced excitotoxicity and ischemia-provoked neurodegeneration. Direct binding of Kinesin-1 to the GluN2B cytoplasmic tails regulated levels of NMDAR at extrasynaptic sites and the subsequent influx of calcium mediated by extrasynaptic NMDAR via regulating the insertion of NMDARs into neuronal surface. Transient increase of Kif5b restored the surface levels of NMDAR and the decreased neuronal susceptibility to NMDA-induced excitotoxicity. Our findings reveal that kinesin-1 regulates extrasynaptic NMDAR targeting and signaling, and the reduction of kinesin-1 could be regulated by neural activity and could be exploited to postpone or halt neurodegeneration.

neuroscience↗

bioRxiv2018

Specification of diverse cell types during early neurogenesis of the mouse cerebellum

We applied single-cell RNA sequencing to profile genome-wide gene expression in about 9,400 individual cerebellar cells from the mouse embryo at embryonic day 13.5. Reiterative clustering identified the major cerebellar cell types and subpopulations of different lineages. Through pseudotemporal ordering to reconstruct developmental trajectories, we identified novel transcriptional programs controlling cell fate specification of populations arising from the ventricular zone and the anterior rhombic lip, two distinct germinal zones of the embryonic cerebellum. Together, our data revealed cell-specific markers for studying the cerebellum, important specification decisions, and a number of previously unknown subpopulations that may play an integral role in the formation and function of the cerebellum. Importantly, we identified a potential mechanism of vermis formation, which is affected by multiple congenital cerebellar defects. Our findings will facilitate new discovery by providing insights into the molecular and cell type diversity in the developing cerebellum.

developmental biology↗

bioRxiv2018

The ghr-miR164 and GhNAC100 module participates in cotton plant defence against Verticillium dahliae

Previous reports have shown that many miRNAs were identified at the early induction stage during which Verticillium dahliae localizes at the root surface. In this study, we constructed two sRNA libraries of cotton root responses to this fungus at the later induction stage when the pathogen enters the root vascular tissue. We identified 71 known miRNAs and 378 novel miRNAs from two pathogen-induced sRNAs and the control libraries. Combined with degradome and sRNA sequencing, 178 corresponding miRNA target genes were identified, in which 40 target genes from differentially expressed miRNAs were primarily associated with oxidation-reduction and stress responses. More importantly, we characterized the ghr-miR164-GhNAC100 module in the response of the plant to V dahliae infection. A GUS fusion reporter showed that ghr-miR164 directly cleaved the mRNA of GhNAC100 in the post-transcriptional process. ghr-miR164-silencing increased the resistance of the plant to this fungus, while the knockdown of GhNAC100 elevated the susceptibility of the plant, indicating that ghr-miR164-GhNAC100 modulates plant defence through the post-transcriptional regulation. Our data documented that there are numerous miRNAs at the later induction stage that participate in the plant response to V. dahliae, suggesting that miRNAs play important roles in plant resistance to vascular disease.\n\nHighlightAccording to degradome and sRNA sequencings of cotton root in responses to Verticillium dahliae at the later induction stage, many miRNAs and corresponding targets including ghr-miR164-GhNAC100 module participate plant defence.

molecular biology↗

bioRxiv2018

Solving the riddle of the evolution of Shine-Dalgarno based translation in chloroplasts

The chloroplast, a photosynthetic organelle found in all plant and algae species, originates from an ancient event in which a cyanobacterium was engulfed by a larger eukaryote. Thus, modern chloroplasts still harbor a bacterial-like genome and carry out all stages of gene expression, including mRNA translation by a 70S ribosome. However, the Shine-Dalgarno model, which predominantly regulates translation initiation by base-pairing between the ribosomal RNA and the mRNA in model bacteria genera, was reported to have ambiguous effects on chloroplast gene expression. Here we show that while the Shine-Dalgarno motif is clearly conserved in proteobacterial mRNAs, its general absence from chloroplast mRNAs is observed in cyanobacteria as well, promoting the idea that the evolutionary process of reducing the centrality of the Shine-Dalgarno mechanism began well before plastid endosymbiosis. As plastid ribosomal RNA anti-Shine-Dalgarno elements are highly similar to their bacterial counterparts, these sites alone cannot explain the decline in plastid Shine-Dalgarno generality. However, by computational simulation we show that upstream point mutations modulate the local structure of ribosomal RNA in chloroplasts, creating significantly tighter structures around the anti-Shine-Dalgarno locus, which in-turn reduce the probability of ribosome binding via the Shine-Dalgarno mechanism. To validate our model, we expressed a mCherry gene harboring a Shine-Dalgarno motif in the Chlamydomonas reinhardtii chloroplast. We show that co-expressing it with a 16S ribosomal RNA, modified according to our model, significantly enhances its expression compared to co-expression with an endogenous 16S gene.\n\nSignificance statementChloroplasts are fascinating intracellular organelles which have evolved from an ancient cyanobacterium engulfed by a larger eukaryote. Surprisingly, the canonical mechanism regulating bacterial translation initiation - Shine-Dalgarno - has been shown to play a reduced role in chloroplasts. Here, we show that mutations upstream from the anti-Shine-Dalgarno element decrease the probability of spontaneous ribosome binding by modulating the secondary structure of the ribosomal RNA. These mutations constitute a regulatory step which acclimates the Shine-Dalgarno mechanism to the translational regulation regime of chloroplasts. Interestingly, we show that these chloroplast features occur in modern cyanobacteria as well, promoting the idea that they have evolved prior to endosymbiosis.

plant biology↗

bioRxiv2018

Using digital epidemiology methods to monitor influenza-like illness in the Netherlands in real-time: the 2017-2018 season

IntroductionDespite the early development of Google Flu Trends in 2009, digital epidemiology methods have not been adopted widely, with most research focusing on the USA. In this article we demonstrate the prediction of real-time trends in influenza-like illness (ILI) in the Netherlands using search engine query data.\n\nMethodsWe used flu-related search query data from Google Trends in combination with traditional surveillance data from 40 general sentinel practices to build our predictive models. We introduced an artificial 4-week delay in the use of GP data in the models, in order to test the predictive performance of the search engine data.\n\nSimulating the weekly use of a prediction model across the 2017/2018 flu season we used lasso regression to fit 52 prediction models (one for each week) for weekly ILI incidence. We used rolling forecast cross-validation for lambda optimization in each model, minimizing the maximum absolute error.\n\nResultsThe models accurately predicted the number of ILI cases during the 2017/18 ILI epidemic in real time with a mean absolute error of 1.40 (per 10,000 population) and a maximum absolute error of 6.36. The model would also have identified the onset, peak, and end of the epidemic with reasonable accuracy\n\nThe number of predictors that were retained in the prediction models was small, ranging from 3 to 5, with a single keyword ( Griep = Flu) having by far the most weight in all models.\n\nDiscussionThis study demonstrates the feasibility of accurate real-time ILI incidence predictions in the Netherlands using internet search query data. Digital ILI monitoring strategies may be useful in countries with poor surveillance systems, or for monitoring emergent diseases, including influenza pandemics. We hope that this transparent and accessible case study inspires and supports further developments in field of digital epidemiology in Europe and beyond.

epidemiology↗

bioRxiv2018

Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias

When collecting large neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because of the limited capacity of a single site. However, site differences represent the greatest barrier when acquiring multi-site neuroimaging data. We utilized a traveling-subject dataset in conjunction with a multi-site, multi-disorder dataset to demonstrate that site differences are composed of biological sampling bias and engineering measurement bias. Effects on resting-state functional MRI connectivity because of both bias types were greater than or equal to those because of psychiatric disorders. Furthermore, our findings indicated that each site can sample only from among a subpopulation of participants. This result suggests that it is essential to collect large neuroimaging data from as many sites as possible to appropriately estimate the distribution of the grand population. Finally, we developed a novel harmonization method that removed only the measurement bias by using traveling-subject dataset and achieved the reduction of the measurement bias by 29% and the improvement of the signal to noise ratios by 40%.

neuroscience↗

bioRxiv2018

Activation of the endoplasmic reticulum unfolded protein response reverses an inflammation-like response to cytoplasmic DNA

Innate immune responses protect organisms against various insults, but may lead to tissue damage when aberrantly activated. In higher organisms, cytoplasmic DNA can trigger inflammation that can lead to tissue degeneration. Simpler in vivo models could shed new mechanistic light on how inflammatory responses to cytoplasmic DNA lead to pathology. Here we show that in DNase II-deficient Caenorhabditis elegans, persistent foreign cytoplasmic DNA leads to systemic tissue degeneration, and we identify impaired protein homeostasis as an inflammatory pathomechanism. This pathological outcome can be alleviated by improving protein homeostasis, either via ectopic induction of the endoplasmic reticulum unfolded protein response (UPRER) or by treatment with N-acetylglucosamine. Our results establish C. elegans as an ancestral metazoan model for studying outcomes of inflammation-like conditions caused by persistent cytoplasmic DNA and provide insight into potential therapies for conditions involving chronic inflammation.

cell biology↗

bioRxiv2018

Aminoacyl tRNA Synthetases as Malarial Drug Targets: A Comparative Bioinformatics Study

Treatment of parasitic diseases has been challenging due to the development of drug resistance by parasites, and thus there is need to identify new class of drugs and drug targets. Protein translation is important for survival of plasmodium and the pathway is present in all the life cycle stages of the plasmodium parasite. Aminoacyl tRNA synthetases are primary enzymes in protein translation as they catalyse the first reaction where an amino acid is added to the cognate tRNA. Currently, there is limited research on comparative studies of aminoacyl tRNA synthetases as potential drug targets. The aim of this study is to understand differences between plasmodium and human aminoacyl tRNA synthetases through bioinformatics analysis. Plasmodium falciparum, P. fragile, P. vivax, P. ovale, P. knowlesi, P. bergei, P. malariae and human aminoacyl tRNA synthetase sequences were retrieved from UniProt database and grouped into 20 families based on amino acid specificity. Despite functional and structural conservation, multiple sequence analysis, motif discovery, pairwise sequence identity calculations and molecular phylogenetic analysis showed striking differences between parasite and human proteins. Prediction of alternate binding sites revealed potential druggable sites in PfArgRS, PfMetRS and PfProRS at regions that were weakly conserved when compared to the human homologues. These differences provide a basis for further exploration of plasmodium aminoacyl tRNA synthetases as potential drug targets.

bioinformatics↗