Essential guidelines for computational method benchmarking

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.Comment: Minor update

Essential guidelines for computational method benchmarking

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology

Dietary soy and meat proteins induce distinct physiological and gene expression changes in rats

This study reports on a comprehensive comparison of the effects of soy and meat proteins given at the recommended level on physiological markers of metabolic syndrome and the hepatic transcriptome. Male rats were fed semi-synthetic diets for 1 wk that differed only regarding protein source, with casein serving as reference. Body weight gain and adipose tissue mass were significantly reduced by soy but not meat proteins. The insulin resistance index was improved by soy, and to a lesser extent by meat proteins. Liver triacylglycerol contents were reduced by both protein sources, which coincided with increased plasma triacylglycerol concentrations. Both soy and meat proteins changed plasma amino acid patterns. The expression of 1571 and 1369 genes were altered by soy and meat proteins respectively. Functional classification revealed that lipid, energy and amino acid metabolic pathways, as well as insulin signaling pathways were regulated differently by soy and meat proteins. Several transcriptional regulators, including NFE2L2, ATF4, Srebf1 and Rictor were identified as potential key upstream regulators. These results suggest that soy and meat proteins induce distinct physiological and gene expression responses in rats and provide novel evidence and suggestions for the health effects of different protein sources in human diets

Identification of putative nuclear receptors and steroidogenic enzymes in Murray-Darling rainbowfish (Melanotaenia fluviatilis) using RNA-Seq and de novo transcriptome assembly

Murray-Darling rainbowfish (Melanotaenia fluviatilis [Castelnau, 1878]; Atheriniformes: Melanotaeniidae) is a small-bodied teleost currently under development in Australasia as a test species for aquatic toxicological studies. To date, efforts towards the development of molecular biomarkers of contaminant exposure have been hindered by the lack of available sequence data. To address this, we sequenced messenger RNA from brain, liver and gonads of mature male and female fish and generated a high-quality draft transcriptome using a de novo assembly approach. 149,742 clusters of putative transcripts were obtained, encompassing 43,841 non-redundant protein-coding regions. Deduced amino acid sequences were annotated by functional inference based on similarity with sequences from manually curated protein sequence databases. The draft assembly contained protein-coding regions homologous to 95.7% of the complete cohort of predicted proteins from the taxonomically related species, Oryzias latipes (Japanese medaka). The mean length of rainbowfish protein-coding sequences relative to their medaka homologues was 92.1%, indicating that despite the limited number of tissues sampled a large proportion of the total expected number of protein-coding genes was captured in the study. Because of our interest in the effects of environmental contaminants on endocrine pathways, we manually curated subsets of coding regions for putative nuclear receptors and steroidogenic enzymes in the rainbowfish transcriptome, revealing 61 candidate nuclear receptors encompassing all known subfamilies, and 41 putative steroidogenic enzymes representing all major steroidogenic enzymes occurring in teleosts. The transcriptome presented here will be a valuable resource for researchers interested in biomarker development, protein structure and function, and contaminant-response genomics in Murray-Darling rainbowfish

Predictions Generated from a Simulation Engine for Gene Expression Micro-arrays for use in Research Laboratories

In this paper we introduce the technical components, the biology and data science involved in the use of microarray technology in biological and clinical research. We discuss how laborious experimental protocols involved in obtaining this data used in laboratories could benefit from using simulations of the data. We discuss the approach used in the simulation engine from [7]. We use this simulation engine to generate a prediction tool in Power BI, a Microsoft, business intelligence tool for analytics and data visualization [22]. This tool could be used in any laboratory using micro-arrays to improve experimental design by comparing how predicted signal intensity compares to observed signal intensity. Signal intensity in micro-arrays is a proxy for level of gene expression in cells. We suggest further development avenues for the prediction tool

THE XENOBIOTIC TRANSCRIPTION FACTOR CAP N COLLAR C REGULATES EXPRESSION OF MULTIPLE INSECTICIDE RESISTANT GENES

Insecticide resistance is a global problem. Insecticide resistance management is very important, considering the time, effort, and cost of discovering and developing a new insecticide. There are diverse resistance mechanisms, but enhanced detoxification through overexpression of cytochrome P450s and target site insensitivity through mutation in insecticide binding site are the two most common mechanisms. The xenobiotic detoxification is divided into three successive phases (I, II and III), which ensures the metabolism and excretion of the detrimental toxins. Each phase comprises of a specific group of metabolizing enzymes such as P450s (phase I), GSTs (phase II) and ABC transporters (phase III). The major goal of my research was to understand the molecular mechanism of insecticide resistance in two economically important coleopteran pests, Leptinotarsa decemlineata and Tribolium castaneum. The transcriptional regulation of the P450 genes mediating insecticide resistance in L. decemlineata (imidacloprid-resistant) and T. castaneum (deltamethrin-resistant) were studied and the xenobiotic trans and cis-elements identified. RNA interference (RNAi), and reporter assays revealed that the cytochrome P450 genes involved in insecticide resistance are regulated by transcription factor Cap n Collar ‘CncC’ and muscle aponeurosis fibromatosis ‘Maf’ belonging to the b-ZIP transcription factor family. Site-directed mutagenesis was employed to identify the binding site for CncC and Maf. Sequencing of RNA isolated from CncC knockdown T. castaneum identified genes regulated by CncC and involved in insecticide detoxification. RNAi and insecticide bioassays confirmed the function of select phase II (glutathione-S-transferases) and phase III (ABC transporters) identified by RNA sequencing. Overall, these data revealed that the xenobiotic transcription factor CncC is the master regulator of multiple genes that are involved in insecticide resistance

L7Ae- and LSm-RNA interactomes of Sulfolobus acidocaldarius

The archaeal L7Ae and Sm-like proteins (LSm) are universal RNA-binding proteins. L7Ae stabilizes non-coding RNA species, including ribosomal RNA, by recognizing a structural RNA motif, termed kink-turn (k-turn). Sm family proteins, like bacterial Hfq and eukaryotic Sm/LSm, are involved in multiple RNA-related processes including small RNA (sRNA)-based translational regulation, mRNA decay or splicing. However, the function of the archaeal members is elusive. Using RNA-immunoprecipitation sequencing (RIP-Seq) methodology, this thesis aimed to identify the global RNA interaction partners (RNA interactome) of L7Ae and the three LSm proteins of the thermoacidophilic archaeon Sulfolobus acidocaldarius. Besides many known non-coding RNAs, the SRP RNA was identified as a novel binding partner of the L7Ae protein. Mobility shift assays demonstrated L7Ae binding to a k-turn motif that was found to be conserved among archaeal SRP RNAs. Interestingly, mRNAs, including the l7ae transcript, were enriched in the RIP-Seq analysis and found to comprise putative k-turns that facilitate L7Ae binding. In vivo studies showed that L7Ae autoregulates the translation of its mRNA by binding to a k-turn motif in the 5' untranslated region. A GFP reporter system was established in Escherichia coli that verified the conservation of L7Ae-mediated feedback regulation in archaea and provides a new tool for the modulation of synthetic gene circuits in bacteria. Mobility shift assays confirmed binding of L7Ae to a k-turn in the transcript of nop5-fibrillarin, suggesting that the synthesis of all C/D box sRNP core proteins (L7Ae, Nop5 and fibrillarin) is regulated by L7Ae. These studies revealed the regulation of mRNA translation as a novel function of the archaeal L7Ae protein. The LSm RIP-Seq study found mRNAs and sRNAs as LSm1 and LSm2 interactors, including a recently reported sRNA that regulates biofilm formation in S. acidocaldarius. No RNA-binding capacity was observed for LSm3. A computational analysis of the interaction partners identified the U-rich 3' termination signal of RNAs and a motif composed of UAG triplets as potential LSm binding sites, which was verified by mobility shift assays. Knock-out studies revealed that only the lsm3 gene is dispensable, whereas the genes for lsm1 and lsm2 seem to be essential. Mutant strains producing tagged versions of LSm1 and LSm2 displayed a pleiotropic phenotype. In resemblance to the roles of bacterial Hfq and eukaryotic LSm proteins, this study provides hints that archaeal LSm proteins may be involved in mRNA degradation, C/D box sRNA biogenesis and sRNA-regulated processes, like tRNA maturation and translational regulation of mRNAs

Investigating novel mechanisms for transcriptional memory using genetic engineering

Transcriptional memory is phenomenon that has gained interest due to its potential impact on human health. With our work, we wanted to contribute to the understanding of its regulation. To do so, we performed genome-wide knockout screens in both budding yeast and human cells. For that, we developed experimental platforms selecting an easy- to-assay readout that allowed us to stratify mutants based on phenotype and scrutinize for mutants enriched or depleted in the corresponding strata. Saccharomyces cerevisiae has been used for many years in genetics mainly because it is a simple unicellular eukaryote that is very easy to manipulate genetically. This made it a very useful model to study fundamental processes of gene expression in eukaryotes, such as transcriptional memory. We have discovered a new layer of complexity to the regulation of this phenomenon in yeast, based on mRNA stability. Despite the great utility of yeast as a model, the translation of the results to humans is challenging. When studying human cellular models, the biology is closer to the real situation in a human being while keeping it still relatively easy to work with. However, there was still a big challenge: precise and easy genetic manipulation. The discovery of the bacterial CRISPR systems and its application to genetic manipulation of high eukaryotes has paved the path to a whole new era in research. It can be used to knock in or knock out genes or intergenic regions of interest, edition, overexpression, epigenetic modifications, and many more. It has potential not only for fundamental research but also for synthetic biology, gene therapy, diagnostics, personalized medicine, etc. In this thesis, we have used a CRISPR/Cas-generated genome-wide knockout pool to interrogate factors involved in transcriptional memory in human cells. We have identified two putative factors involved in the regulation of transcriptional memory in humans that are interesting candidates for further research. To validate and further investigate candidates identified in pooled screens, knockout cell lines are frequently produced. A common method for that, is introducing two adjacent DNA double strand breaks (DSBs), using for example CRISPR/Cas with two gRNAs, that often results in the loss of the region in between. We have uncovered the occurrence of unexpected on-target aberrations while using a dual guide CRISPR/Cas system to produce deletion knockouts. We have shown that these events can go unseen and affect the phenotype of the cells. We proposed a workflow for comprehensive analysis of deletion clones. Finally, in 2020, scientists across the word were urged to help in the SARS‐CoV‐2 pandemic. As the virus spread quickly, it was crucial to combine the therapeutic efforts with the development of diagnostic tools. The gold standard detection method, RT-qPCR is very sensitive and specific, but is expensive and requires specialized equipment not available in all contexts. In addition, the reagents providers promptly started struggling to meet the global demand. The scientific community responded developing a plethora of alternatives. Some of those methods are based on loop-mediated isothermal amplification (LAMP) of the viral RNA, which can be detected either by fluorescence or change in pH among others. Compared to RT-qPCR, this technic is faster and cheaper, with a simple readout that does not require specific equipment. However, it still required the extraction of the viral RNA, and the supply of related reagents was rapidly affected. Here, we developed a LAMP-based method to detect SARS‐CoV‐2 without any previous manipulation of the sample, using in-house produced enzymes. Our method performs comparatively to the commercially available options in terms of sensitivity and specificity, and it is compatible with the most commonly used sample carriers. All the plasmids for the production of the enzymes used are publicly available

Characterization of Human Gut Microbiota Dynamics Using Model Communities in Gnotobiotic Mice

The human gut is colonized by a diverse array of microbes, collectively referred to as the microbiota. The microbiota\u27s complexity poses significant challenges in characterizing the rules dictating its assembly, inferring the functional roles of its component species, and understanding how communities sense and respond to changes in their habitat. We developed defined, representative model communities comprised of sequenced human gut bacteria that could be characterized in a highly controlled manner in gnotobiotic mice, plus a suite of scalable molecular tools for assaying community properties. These tools were first used to evaluate how the microbiota is impacted by probiotic bacterial strains found in fermented milk products: FMP). Introduction of a consortium of five FMP strains resulted in only minimal changes in the structural configuration of a 15-member model microbiota. However, RNA-Seq and follow-up mass spectrometry revealed numerous functional responses, many related to carbohydrate metabolism. Results from a study performed in monozygotic twin pairs confirmed many of our observations in the model microbiota, showing that lessons learned from preclinical models can inform the design and interpretation of human studies. In a second set of experiments, we evaluated the impact of food on both a model community and its constituent taxa by feeding gnotobiotic mice oscillating diets of disparate composition. In addition to prompt and reversible structural reconfigurations suggesting rules-based diet effects, we noted consistent, staggered changes in the representation of many functions within the metatranscriptome related to carbohydrate and amino acid metabolism. One prominent community member, Bacteroides cellulosilyticus WH2, was identified as an adaptive forager that tailors its versatile carbohydrate utilization strategy to the dietary polysaccharides available. The specific carbohydrates that trigger expression of many of this organism\u27s 113 predicted polysaccharide utilization loci were identified by RNA-Seq analysis during in vitro growth on 31 distinct carbohydrate substrates, aiding our interpretation of in vivo RNA-Seq and high resolution proteomics data. These results offer insight into how gut microbes adapt to dietary perturbations, both at a community level and from the perspective of a well-adapted symbiont with exceptional saccharolytic capabilities, and illustrate the value of studying defined models of the human gut microbiota

The Galleria mellonella Hologenome Supports Microbiota-Independent Metabolism of Long-Chain Hydrocarbon Beeswax

The greater wax moth, Galleria mellonella, degrades wax and plastic molecules. Despite much interest, the genetic basis of these hallmark traits remains poorly understood. Herein, we assembled high-quality genome and transcriptome data from G. mellonella to investigate long-chain hydrocarbon wax metabolism strategies. Specific carboxylesterase and lipase and fatty-acid-metabolism-related enzymes in the G. mellonella genome are transcriptionally regulated during feeding on beeswax. Strikingly, G. mellonella lacking intestinal microbiota successfully decomposes long-chain fatty acids following wax metabolism, although the intestinal microbiome performs a supplementary role in short-chain fatty acid degradation. Notably, final wax derivatives were detected by gas chromatography even in the absence of gut microbiota. Our findings provide insight into wax moth adaptation and may assist in the development of unique wax-degradation strategies with a similar metabolic approach for a plastic molecule polyethylene biodegradation using organisms without intestinal microbiota. The evolutionarily expanded long-chain fatty acid degradation gene products of Galleria mellonella decompose long-chain hydrocarbons independently of intestinal microorganisms. Kong et al. show that beeswax and degradation products are detected equally in larvae in the presence or absence of intestinal microbes