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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Liver ultrasound elastography for the evaluation of periportal fibrosis in schistosomiasis mansoni: A cross-sectional study

BackgroundARFI elastrography has been used as a noninvasive method to assess the severity of liver fibrosis in viral hepatitis, although with few studies in schistosomiasis mansoni. We aimed to evaluate the performance of point shear wave elastography (pSWE) for predicting significant periportal fibrosis (PPF) in schistosomotic patients and to determine its best cutoff point.\n\nMethodology/Principal findingsThis cross-sectional study included 358 adult schistosomotic patients subjected to US and pSWE on the right lobe. Two hundred two patients (62.0%) were women, with a median age of 54 (ranging 18-92) years. The pSWE measurements were compared to the US patterns of PPF, as gold standard, according to the Niamey classification. The performance of pSWE was calculated as the area under the ROC curve (AUC). Patients were further classified into two groups: 86 patients with mild PPF and 272 patients with significant PPF. The median pSWE of the significant fibrosis group was higher (1.40 m/s) than that of mild fibrosis group (1.14 m/s, p<0.001). AUC was 0.719 with [≤]1.11 m/s as the best cutoff value for excluding significant PPF. Sensitivity and negative predictive values were 80.5% and 40.5%, respectively. Whereas, for confirming significant PPF, the best cutoff value was >1.39 m/s, with specificity of 86.1% and positive predictive value of 92.0%.\n\nConclusions/SignificancepSWE was able to differentiate significant from mild PPF, with better performance to predict significant PPF.\n\nAuthor summaryIn the developing world, over 207 million people are infected with parasitic Schistosoma worms. Among the species of Schistosoma that infect humans Schistosoma mansoni is one of the most common causes of illness. Here, we investigated the performance of point shear wave elastography (pSWE) for predicting significant periportal fibrosis (PPF) in schistosomotic patients and to determine its best cutoff point. We examined 358 people from northeast of Brazil for Schistosoma infections. The present study showed that pSWE was able to differentiate significant from mild PPF, with better performance to predict significant PPF.

bioengineering↗

bioRxiv2018

Prediction of Algal Blooms in the Great Lakes through a Convolution Neural Network of Remote Sensing Data

Harmful algal blooms (HABs) are the proliferation of algae due to eutrophication and have severe repercussions to the ecological balance in many water bodies, due to the toxins the algae produce. Additionally, the identification and prediction of these HABs has been a challenge in the scientific community due to the interactions between both biological and physical processes that cause the HABs. Here, we used remote sensing data to bypass these issues; remote sensing data provides significant information about the coverage of chlorophyll which can be used to locate HABs. Using this indicator of HABs, we trained a Convolution Neural Network (CNN) to identify nine types of algal blooms, using 25 epochs of 900 images, which can predict algal bloom shapes with an 80 percent accuracy. This approach of HAB identification can easily be applied to other aquatic ecosystems where remote sensing data is present.

ecology↗

bioRxiv2018

Immigration from the metacommunity affects bdelloid rotifer community dynamics most

Dispersal is an important driver of local community dynamics. It has been proposed that, for communities composed of microscopic organisms, dispersal could well be the dominant process, outpacing local processes driven by environmental conditions and species interactions. This is because microscopic organisms often reproduce asexually, fostering rapid colonization, and are easily dispersed by water or air current. We studied the case of bdelloid rotifers belonging to the genus Adineta, microscopic asexual animals with dried stages that are easily dispersed by wind to investigate the relative effects of dispersal and local processes on their community dynamics. To this end, we constructed a classic competition model to theoretically examine how spatial and local biodiversity dynamics varied with fitness and dispersal characteristics of bdelloid Adineta species. Next, we compared our predictions with an experimental dataset containing spatio-temporal Adineta community dynamics from the wild. This comparison suggested that immigration from the local meta-community was the most critical parameter under the conditions tested. One Adineta vaga species, abundant in the surrounding area, rapidly colonized our experimental habitats and dominated most of the communities. We also ran the model under different levels of environmental conditions (permissive, intermediate and harsh) to simulate seasonal community variability and found that communities experience important bottlenecks yearly in winter but that the same community re-established. The dissimilarities observed between roof communities suggest differences in adaptation or immigration capacities. Besides their asexual reproduction and extreme desiccation tolerance, a key characteristic of bdelloid ecology identified here, is the spatio-temporal dynamic of abundant bdelloid clones present in the meta-community that rapidly colonize empty patches to establish new populations.

ecology↗

bioRxiv2018

MR-PET head motion correction based on co-registration of multi-contrast MR images

Head motion is a major source of image artefacts in neuroimaging studies and can lead to degradation of the quantitative accuracy of reconstructed PET images. Simultaneous Magnetic Resonance-Positron Emission Tomography (MR-PET) makes it possible to estimate head motion information from high-resolution MR images and then correct motion artefacts in PET images. In this paper, we introduce a fully automated PET motion correction method, MR-guided MAF, based on the co-registration of multi-contrast MR images. The performance of the MR-guided MAF method was evaluated using MR-PET data acquired from a cohort of ten healthy participants who received a slow infusion of fluorodeoxyglucose ([18-F]FDG). Compared with conventional methods, MR guided PET image reconstruction can reduce head motion introduced artefacts and improve the image sharpness and quantitative accuracy of PET images acquired using simultaneous MR-PET scanners. The fully automated motion estimation method has been implemented as a publicly available web-service.

bioinformatics↗

bioRxiv2018

The global diversity of a major parasitic nematode is shaped by human intervention and climatic adaptation

The gastrointestinal parasite Haemonchus contortus is an haematophagous parasitic nematode of veterinary interest and a model for the study of drug resistance mechanisms or host-parasite interactions. To understand its evolutionary history, and its ability to adapt in the face of climatic and drug pressure, we have performed an extensive survey of genome-wide diversity using single-worm whole genome sequencing of 223 individuals sampled from 19 isolates spanning five continents. The pattern of global diversity is driven by an African origin for the species, together with contemporary dispersal that is consistent with modern human movement, with evidence for parasites spreading during the transatlantic slave trade and colonisation of Australia presented. Strong selective sweeps were identified in independent populations each surrounding the {beta}-tubulin locus, a target of benzimidazole anthelmintic drug treatment used widely to control H. contortus infections. These signatures of selection were further supported by signals of diversifying selection enriched in genes involved in response to drugs, as well as other anthelmintic-associated biological functions including pharyngeal pumping and oviposition. From these analyses, we identify some known, and previously undescribed, candidate genes that may play a role in ivermectin resistance. Finally, we describe genetic signatures of climate-driven adaptation, revealing a gene acting as an epigenetic regulator and components of the dauer pathway may play a role in adaptation in the face of climatic fluctuations. These results begin to define genetic adaptation to climate for the first time in a parasitic nematode, and provides insight into the ongoing expansion in the range of Haemonchus contortus, which may have consequences for the management of this parasite.

genomics↗

bioRxiv2018

Microbiota profiling with long amplicons using Nanopore sequencing: full-length 16S rRNA gene and whole rrn operon

BackgroundProfiling microbiome on low biomass samples is challenging for metagenomics since these samples are prone to present DNA from other sources, such as the host or the environment. The usual approach is sequencing specific hypervariable regions of the 16S rRNA gene, which fails to assign taxonomy to genus and species level. Here, we aim to assess long-amplicon PCR-based approaches for assigning taxonomy at the genus and species level. We use Nanopore sequencing with two different markers: full-length 16S rRNA ([~]1,500 bp) and the whole rrn operon (16S rRNA gene - ITS - 23S rRNA gene; 4,500 bp).\n\nMethodsWe sequenced a clinical isolate of Staphylococcus pseudintermedius, two mock communities (HM-783D, Bei Resources; D6306, ZymoBIOMICS) and two pools of lowbiomass samples (dog skin). Nanopore sequencing was performed on MinION (Oxford Nanopore Technologies) using 1D PCR barcoding kit. Sequences were pre-processed, and data were analyzed using WIMP workflow on EPI2ME (ONT) or Minimap2 software with rrn database.\n\nResultsFull-length 16S rRNA and the rrn operon retrieved the microbiota composition from the bacterial isolate, the mock communities and the complex skin samples, even at the genus and species level. For Staphylococcus pseudintermedius isolate, when using EPI2ME, the amplicons were assigned to the correct bacterial species in [~]98% of the cases with rrn operon as the marker, and [~]68% of the cases with 16S rRNA gene respectively. In both skin microbiota samples, we detected many species with an environmental origin. In chin, we found different Pseudomonas species in high abundance, whereas in dorsal skin there were more taxa with lower abundances.\n\nConclusionsBoth full-length 16S rRNA and the rrn operon retrieved the microbiota composition of simple and complex microbial communities, even from the low-biomass samples such as dog skin. For an increased resolution at the species level, rrn operon would be the best choice.

microbiology↗

bioRxiv2018

Single nucleotide polymorphisms of the c-MYC gene’s relationship with formation of Burkitt’s lymphoma using bioinformatics analysis

Burkitts lymphoma (BL) is an aggressive form of non-Hodgkin lymphoma, originates from germinal center B cells, MYC gene (MIM ID 190080) is an important proto-oncogene transcriptional factor encoding a nuclear phosphoprotein for central cellular processes. Dysregulated expression or function of c-MYC is one of the most common abnormalities in BL. This study focused on the investigation of the possible role of single nucleotide polymorphisms (SNPs) in MYC gene associated with formation of BL.\n\nMYC SNPs were obtained from NCBI database. SNPs in the coding region that are non-synonymous (nsSNPs) were analysed by multiple programs such as SIFT, Polyphen2, SNPs&GO, PHD-SNP and I-mutant. In this study, a total of 286 Homo sapiens SNPs were found. Roughly, forty-eight of them were deleterious and were furtherly investigated.\n\nEight SNPs were considered most disease causing [rs4645959 (N26S), rs4645959 (N25S), rs141095253 (P396L), rs141095253 (P397L), rs150308400 (C233Y), rs150308400 (C147Y), rs150308400 (C147Y), rs150308400 (C148Y)] according to the four softwares used. Two of which have not been reported previously [rs4645959 (N25S), rs141095253 (P396L)]. SNPs analysis helps is a diagnostic marker which helps in diagnosing and consequently, finding therapeutics for clinical diseases. This is through SNPs genotyping arrays and other techniques. Thus, it is highly recommended to confirm the findings in this study in vivo and in vitro.

bioinformatics↗

bioRxiv2018

DNA barcodes for rapid, whole genome, single-molecule analyses

We report an approach for visualizing DNA sequence and using these DNA barcodes to search complex mixtures of genomic material for DNA molecules of interest. We demonstrate three applications of this methodology; by identifying specific molecules of interest from a dataset containing gigabasepairs of genome; by straightforward strain-typing of bacteria from such a dataset and, finally, by locating infecting virus molecules in a background of human genomic material. DNA barcodes enable quantitative understanding of complex genome mixtures, on a large scale. As a result of the dense fluorescent labelling of the DNA, individual barcodes of the order 40 kilobase pairs in length can be reliably identified. This means DNA can be prepared for imaging using standard handling and purification techniques. The recorded dataset provides stable physical and electronic records of the total genomic content of a sample that can be readily searched for a molecule or region of interest.

genomics↗

bioRxiv2018

Production of glycine-derived ammonia as a low-cost and long-distance antibiotic strategy by Streptomyces

Soil-inhabiting streptomycetes are Natures medicine makers, producing over half of all known antibiotics and many other bioactive natural products. However, these bacteria also produce many volatile compounds, and research into these molecules and their role in soil ecology is rapidly gaining momentum. Here we show that streptomycetes have the ability to kill bacteria over long distances via air-borne antibiosis. Our research shows that streptomycetes do so by producing surprisingly high amounts of the low-cost volatile antimicrobial ammonia, which travels over long distances and antagonises both Gram-positive and Gram-negative bacteria. Glycine is required as precursor to produce ammonia, and inactivation of the glycine cleavage system annihilated air-borne antibiosis. As a resistance strategy, E. coli cells acquired mutations resulting in reduced expression of the porin master regulator OmpR and its cognate kinase EnvZ, which was just enough to allow them to survive. We further show that ammonia enhances the activity of the more costly canonical antibiotics, suggesting that streptomycetes adopt a low-cost strategy to sensitize competitors for antibiosis over longer distances.

microbiology↗

bioRxiv2018

Modelling cancer progression using Mutual Hazard Networks

MotivationCancer progresses by accumulating genomic events, such as mutations and copy number alterations, whose chronological order is key to understanding the disease but difficult to observe. Instead, cancer progression models use co-occurence patterns in cross-sectional data to infer epistatic interactions between events and thereby uncover their most likely order of occurence. State-of-the-art progression models, however, are limited by mathematical tractability and only allow events to interact in directed acyclic graphs, to promote but not inhibit subsequent events, or to be mutually exclusive in distinct groups that cannot overlap.\n\nResultsHere we propose Mutual Hazard Networks (MHN), a new Machine Learning algorithm to infer cyclic progression models from cross-sectional data. MHN model events by their spontaneous rate of fixation and by multiplicative effects they exert on the rates of successive events. MHN compared favourably to acyclic models in cross-validated model fit on four datasets tested. In application to the glioblastoma dataset from The Cancer Genome Atlas, MHN proposed a novel interaction in line with consecutive biopsies: IDH1 mutations are early events that promote subsequent fixation of TP53 mutations.\n\nAvailabilityImplementation and data are available at https://github.com/RudiSchill/MHN.

bioinformatics↗

bioRxiv2018

Antigen-specific T-cell receptor signatures of cytomegalovirus infection

Cytomegalovirus (CMV) is a prevalent human pathogen. The virus cannot be eliminated from the body, but is kept in check by CMV-specific T cells. Patients with an insufficient T-cell response, such as transplant recipients, are at high risk of developing CMV disease. However, the CMV-specific T-cell repertoire is complex, and is not yet clear which T cells protect best against virus reactivation and disease. Here we present a highly resolved characterization of CMV-specific CD8+ T cells based on enrichment by specific peptide stimulation and mRNA sequencing of their T-cell receptor {beta} chains (TCR{beta}). Our analysis included recently identified T-cell epitopes restricted through HLA-C, whose presentation is resistant to viral immunomodulation, and well-studied HLA-B-restricted epitopes. In 8 healthy virus carriers, we identified a total of 1052 CMV-specific TCR{beta} chains. HLA-C-restricted, CMV-specific TCR{beta} clonotypes the ex vivo T-cell response, and contributed the highest-frequency clonotype of the entire repertoire in 2 of 8 donors. We analyzed sharing and similarity of CMV-specific TCR{beta} sequences and identified 63 public or related sequences belonging to 17 public TCR{beta} families. In our cohort and in an independent cohort of 352 donors, the cumulative frequency of these public TCR{beta} family members was a highly discriminatory indicator of carrying both CMV infection and the relevant HLA type. Based on these findings, we propose CMV-specific TCR{beta} signatures as a biomarker for an antiviral T-cell response to identify patients in need of treatment and to guide future development of immunotherapy.

immunology↗

bioRxiv2018

AGEpy: a Python package for computational biology

SummaryAGEpy is a Python package focused on the transformation of interpretable data into biological meaning. It is designed to support high-throughput analysis of pre-processed biological data using either local Python based processing or Python based API calls to local or remote servers. In this application note we describe its different Python modules as well as its command line accessible tools aDiff, abed, blasto, david, and obo2tsv.\n\nAvailabilityThe open source AGEpy Python package is freely available at: https://github.com/mpg-age-bioinformatics/AGEpy.\n\nContactjorge.boucas@age.mpg.de

bioinformatics↗

bioRxiv2018

Organ-wide and ploidy-dependent regulations both contribute to cell size determination: evidence from a computational model of tomato fruit

The development of a new organ is the result of coordinated events of cell division and expansion, in strong interaction with each other. This paper presents a dynamic model of tomato fruit development that includes cells division, endoreduplication and expansion processes. The model is used to investigate the interaction among these developmental processes, in the perspective of a neo-cellular theory. In particular, different control schemes (either cell-autonomous or organ-controlled) are tested and results compared to observed data from two contrasted genotypes. The model shows that a pure cell-autonomous control fails to reproduce the observed cell size distribution, and an organ-wide control is required in order to get realistic cell sizes. The model also supports the role of endoreduplication as an important determinant of the final cell size and suggests a possible interaction through carbon allocation and metabolism.

plant biology↗

bioRxiv2018

The effect of presentation level on spectrotemporal modulation detection

The understanding of speech in noise relies (at least partially) on spectrotemporal modulation sensitivity. This sensitivity can be measured by spectral ripple tests, which can be administered at different presentation levels. However, it is not known how presentation level affects spectrotemporal modulation thresholds. In this work, we present behavioral data for normal-hearing adults which show that at higher ripple densities (2 and 4 ripples/oct), increasing presentation level led to worse discrimination thresholds. Results of a computational model suggested that the higher thresholds could be explained by a worsening of the spectrotemporal representation in the auditory nerve due to broadening of cochlear filters and neural activity saturation. Our results demonstrate the importance of taking presentation level into account when administering spectrotemporal modulation detection tests.

neuroscience↗

bioRxiv2018

A physiology-based model of bile acid metabolism shows altered tissue concentrations after drug administration and in specific genotype subgroups

Drug-induced liver injuries (DILI) are an important issue in drug development and patient safety and often lead to termination of drug-development programs or late withdrawals of drugs. Since DILI events are hard to diagnose in preclinical settings, a need for alternative prediction methods such as computational modeling emerges. Impairment of bile acid (BA) metabolism, known as cholestasis, is a frequent form of DILI. Being rather a systemic then a single organ related disease, whole-body physiology-based modeling is a predestined approach for cholestasis modeling. The objectives of the presented study were 1) the development of a physiology-based model for human bile acid metabolism, 2) model validation and characterization for a virtual population, and 3) prediction and quantification of the effects of genetic predispositions and drug interaction on bile acid metabolism. The developed physiology-based bile acid (PBBA) model is based on the standard PBPK model of PKSim(R) and describes the bile acid circulation in a healthy reference individual. Active processes such as the hepatic synthesis, gallbladder emptying upon meal intake, transition through the gastrointestinal tract, reabsorption into the liver, distribution within the body, and excretion are included. The kinetics of active processes for the surrogate BA glycochenodeoxycholic acid were fitted to time-concentration profiles of blood BA levels reported in literature. The robustness of our PBBA model is underlined by the comparison of simulated plasma BA concentrations in a virtual population of 1,000 healthy individuals with reported data. In addition to plasma concentrations, the PBBA model allows simulations of BA exposure in relevant tissues like the liver and can therefore enhance the mechanistic understanding of cholestasis. This feature was used to analyse the reported increased risk of cholestatic DILI in Benign Recurrent Intrahepatic Cholestasis type 2 (BRIC2) patients. Simulations of the PBBA model suggest a higher susceptibility of BRIC2 patients towards cholestatic DILI due to BA accumulation in hepatocytes. Apart from these intrinsic effects, drug-interactions and their effect on the systemic bile acid metabolism were simulated by combining the PBBA model with a drug PBPK model of cyclosporine A (CsA). The results of which confirmed the reported higher risk of developing DILI as a consequence of CsA intake. Altogether, the presented model enhances our mechanistic understanding of cholestasis, allows the identification of drug-interactions leading to altered BA levels in blood and organs, and could be used to prevent clinical cases of cholestasis and enhance patient safety.

systems biology↗

bioRxiv2018

Learning of distant state predictions by the orbitofrontal cortex in humans

Representations of our future environment are essential for planning and decision making. Previous research in humans has demonstrated that the hippocampus is a critical region for forming and retrieving associations, while the medial orbitofrontal cortex (OFC) is an important region for representing information about recent states. However, it is not clear how the brain acquires predictive representations during goal-directed learning. Here, we show using fMRI that while participants learned to find rewards in multiple different Y-maze environments, hippocampal activity was highest during initial exposure and then decayed across the remaining repetitions of each maze, consistent with a role in rapid encoding. Importantly, multivariate patterns in the OFC-VPFC came to represent predictive information about upcoming states approximately 30 seconds in the future. Our findings provide a mechanism by which the brain can build models of the world that span long-timescales to make predictions.

neuroscience↗

bioRxiv2018

Massive gene amplification on a recently formed Drosophila Y chromosome

Widespread loss of genes on the Y is considered a hallmark of sex chromosome differentiation. Here we show that the initial stages of Y evolution are driven by massive amplification of distinct classes of genes. The neo-Y chromosome of Drosophila miranda initially contained about 3000 protein-coding genes, but has gained over 3200 genes since its formation about 1.5 MY ago, primarily by tandem amplification of protein-coding genes ancestrally present on this chromosome. We show that distinct evolutionary processes may account for this drastic increase in gene number on the Y. Testis-specific and dosage sensitive genes appear to have amplified on the Y to increase male fitness. A distinct class of meiosis-related multi-copy Y genes independently co-amplified on the X, and their expansion is likely driven by conflicts over segregation. Co-amplified X/Y genes are highly expressed in testis, enriched for meiosis and RNAi functions, and are frequently targeted by small RNAs in testis. This suggests that their amplification is driven by X vs. Y antagonism for increased transmission, where sex chromosome drive suppression is likely mediated by sequence homology between the suppressor and distorter, through RNAi mechanism. Thus, our analysis suggests that newly emerged sex chromosomes are a battleground for sexual and meiotic conflict.

evolutionary biology↗

bioRxiv2018

Integration of heterogeneous functional genomics data in gerontology research identifies genes and pathway underlying aging across species

Understanding the biological mechanisms behind aging, lifespan and healthspan is becoming increasingly important as the proportion of the world's population over the age of 65 grows, along with the cost and complexity of their care. BigData oriented approaches and analysis methods for integrative functional genomics enable current and future bio-gerontologists to synthesize, distill and interpret vast, heterogeneous data. GeneWeaver is an analysis system for integration of data that allows investigators to store, search, and analyze immense amounts of data including user-submitted experimental data, data from primary publications, and data in other databases. Aging related genome-wide gene sets from primary publications were curated into this system in concert with data from other model-organism and aging-specific databases, and used in several application using GeneWeavers analysis tools. For example, we identified Cd63 as a frequently represented gene among aging-related genome-wide results. To evaluate the role of Cd63 in aging, we performed RNAi knockdown of the C. elegans ortholog, tsp-7, demonstrating that this manipulation is capable of extending lifespan. The tools in GeneWeaver enable aging researchers to make new discoveries into the associations between the genes, normal biological processes, and diseases that affect aging, healthspan, and lifespan.

bioinformatics↗