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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2023

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a novel optimization procedure to identify the optimal network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression. SignificanceA combined bioinformatics and systems-biology modeling approach is designed to model a transcriptional regulatory network for AML with IDH mutations. Network modeling identifies key regulators DNMT1 and E2F1, which is supported by patient survival data.

systems biology↗

bioRxiv2023

Gorse (Ulex europeaus) wastes with 5,6-dimethyl benzimidazole supplementation can support growth of vitamin B12 producing commensal gut microbes

Many commensal gut microbes are recognized for their potential to synthesize vitamin B12, offering a promising avenue to address deficiencies through probiotic supplementation. While bioinformatics tools aid in predicting B12 biosynthetic potential, empirical validation remains crucial to confirm production, identify cobalamin vitamers, and establish biosynthetic yields. This study investigates vitamin B12 production in three human colonic bacterial species: Anaerobu-tyricum hallii DSM 3353, Roseburia faecis DSM 16840, and Anaerostipes caccae DSM 14662, along with Propionibacterium freudenreichii DSM 4902 as a positive control. These strains were selected for their potential use as probiotics, based on speculated B12 production from prior bioinformatic analyses. Cultures were grown in M2GSC, chemically defined media (CDM), and Gorse extract medium (GEM). The composition of GEM was similar to CDM, expect that the carbon and nitrogen source was replaced with protein-depleted liquid wastes obtained after subjecting Gorse to a leaf protein extraction process. B12 yields were quantified using liquid chromatography with tandem mass spectrophotometry. The results suggest that the three butyrate-producing strains could indeed produce B12, although the yields were notably low, and with no B12 being detected in the extracellular media. Next, GEM outperformed the conventional M2GSC growth medium in enhancing B12 production. The positive control, P. freudenreichii DSM 4902 produced B12 at concentrations ranging from 7 ng{middle dot}mL-1 to 12 ng{middle dot}mL-1. Univariate-scaled Principal Component Analysis of data from previous publications investigating B12 production in P. freudenreichii revealed that B12 yields diminished when the carbon source concentration was[≤] 30 g{middle dot}L-1. In conclusion, the protein-depleted wastes from the leaf protein extraction process from Gorse can be valorised as a viable substrate for culturing B12-producing colonic gut microbes. Furthermore, this is the first report attesting to the ability of A. hallii, R. faecis, and A. caccae to produce B12. However, these microbes seem unsuitable for industrial applications owing to low B12 yields.

microbiology↗

bioRxiv2023

Identification and functional characterisation of a locus for target site integration in Fusarium graminearum

BackgroundFusarium Head Blight is a destructive floral disease of different cereal crops. The Ascomycete fungus Fusarium graminearum (Fg) is one of the main causal agents of FHB in wheat and barley. The role(s) in virulence of Fg genes include genetic studies that involve the transformation of the fungus with different expression cassettes. We have observed in several studies where Fg genes functions were characterised that integration of expression cassettes occurred randomly. Random insertion of a cassette may disrupt gene expression and/or protein functions and hence the overall conclusion of the study. Target site integration (TSI) is an approach that consists in identifying a chromosomal region where the cassette can be inserted. The identification of a suitable locus for TSI in Fg would avert the potential risks of ectopic integration. ResultsHere, we identified a highly conserved intergenic region on chromosome 1 suitable for TSI. We named this intergenic region the TSI locus 1. We developed an efficient cloning vector system based on the Golden Gate method to clone different expression cassettes for use in combination with TSI locus 1. We present evidence that integrations in the TSI locus 1 affects neither fungal virulence nor fungal growth under different stress conditions. Integrations at the TSI locus 1 resulted in the expression of different gene fusions. In addition, the activities of Fg native promoters were not altered by integration into the TSI locus 1. We have developed a bespoke bioinformatic pipeline to analyse the existence of ectopic integrations and tandem insertions of the cassette that may occurred during the transformation process. Finally, we established a protocol to study protein secretion in wheat coleoptiles using confocal microscopy and the TSI locus 1. ConclusionThe TSI locus 1 can be used in Fg and potentially other cereal infecting Fusarium species for diverse studies including promoter activity analysis, secretion, protein localisation studies and gene complementation. The bespoke bioinformatic pipeline developed in this work can be an alternative to southern blotting, the gold standard technique to identify ectopic integration and tandem insertions in fungal transformation.

genetics↗

bioRxiv2023

Identification of Cholangiocarcinoma (CCA) Subtype-Specific Biomarkers

Liver cancer ranks sixth globally in diagnoses and second in cancer-related deaths. Cholangiocarcinoma (CCA), a relatively rare cancer originating from bile duct epithelium, constitutes 2% of all cancers, with increasing occurrences in Westerns. Incidence is influenced by inflammation, genetics, risk factors, and regional disparities, with higher rates in the Eastern hemisphere. Diagnostic and prognostic biomarkers are pivotal for effective cancer prevention and management. Recent research explores serum proteins for non-invasive CCA diagnosis and proposes targeted receptor approaches for therapeutics. This study aims to identify these biomarkers via bioinformatics analysis of public datasets, focusing on CCA patient transcriptomes to uncover gene biomarkers linked to age and survival. Pathway analysis reveals functions and pathways associated with these biomarkers. Additionally, the study employs the ESM-TFpredict machine learning model to predict transcription factors (TFs) using protein sequence data. Leveraging publicly available data enhances our understanding of liver cancers molecular profiles and clinical relevance, particularly concerning CCA, This study integrates bioinformatics analysis, transcriptomic exploration, and machine learning to unveil a novel set of potential diagnostic and prognostic biomarkers for CCA.

systems biology↗

bioRxiv2023

Regulation potential of transcribed simple repeated sequences in developing neurons

Simple repeated sequences (SRSs), defined as tandem iterations of microsatellite- to satellite-sized DNA units, occupy a substantial part of the human genome. Some of these elements are known to be transcribed in the context of repeat expansion disorders. Mounting evidence suggests that the transcription of SRSs may also contribute to normal cellular functions. Here, we used genome-wide bioinformatics approaches to systematically examine SRS transcriptional activity in cells undergoing neuronal differentiation. We identified thousands of long noncoding RNAs containing >200-nucleotide-long SRSs (SRS-lncRNAs), with hundreds of these transcripts significantly upregulated in the neural lineage. We show that SRS-lncRNAs often originate from telomere-proximal regions and that they have a strong potential to form multivalent contacts with a wide range of RNA-binding proteins. Our analyses also uncovered a cluster of neurally upregulated SRS-lncRNAs encoded in a centromere-proximal part of chromosome 9, which underwent an evolutionarily recent segmental duplication. Using a newly established in vitro system for rapid neuronal differentiation of induced pluripotent stem cells, we demonstrate that at least some of the bioinformatically predicted SRS-lncRNAs, including those encoded in the segmentally duplicated part of chromosome 9, indeed increase their expression in developing neurons to readily detectable levels. These data suggest that many SRSs may be expressed in a cell type and developmental stage-specific manner, providing a valuable resource for further studies focused on the functional consequences of SRS-lncRNAs in the normal development of the human brain.

genomics↗

bioRxiv2023

Nanopore sequencing for accurate bacterial outbreak tracing

Our study investigated the effectiveness of Oxford Nanopore Technologies for accurate outbreak tracing by resequencing 33 isolates of a three-year-long Klebsiella pneumoniae outbreak with Illumina short read sequencing data as the point of reference. We detected considerable base errors through cgMLST and phylogenetic analysis of genomes sequenced with Oxford Nanopore Technologies, leading to the false exclusion of some outbreak-related strains from the outbreak cluster. Nearby methylation sites cause these errors and can also be found in other species besides K. pneumoniae. Based on this data, we explored PCR-based sequencing and a masking strategy, which both successfully addressed these inaccuracies and ensured accurate outbreak tracing. We offer our masking strategy as a bioinformatic workflow (MPOA is freely available on GitHub under the GNUv3 license: github.com/replikation/MPOA) to identify and mask problematic genome positions in a reference-free manner. Our research highlights limitations in using Oxford Nanopore Technologies for sequencing prokaryotic organisms, especially for investing outbreaks. For time-critical projects that cannot wait for further technological developments by Oxford Nanopore Technologies, our study recommends either PCR-based sequencing or using our provided bioinformatic workflow. We would advise that read mapping-based quality control of genomes should be provided when publishing results.

molecular biology↗

bioRxiv2023

Preclinical exploration of the DNA Damage Response pathway using the interactive neuroblastoma cell line explorer CLEAN.

Neuroblastoma (NB) is the most common cancer in infancy with an urgent need for more efficient targeted therapies. The development of novel (combinatorial) treatment strategies relies on extensive explorations of signaling perturbations in neuroblastoma cell lines, using RNA-Seq or other high throughput technologies (e.g., phosphoproteomics). This typically requires dedicated bioinformatics support, which is not always available. Additionally, while data from published studies are highly valuable and raw data (e.g., fastq files) are nowadays released in public repositories, data processing is time-consuming and again difficult without bioinformatics support. To facilitate NB research, more user-friendly and immediately accessible platforms are needed to explore newly generated as well as existing high throughput data. To make this possible, we developed an interactive data centralization and visualization web application, called CLEAN (the Cell Line Explorer web Application of Neuroblastoma data; https://ccgg.ugent.be/shiny/clean/). By focusing on the regulation of the DNA damage response, a therapeutic target of major interest in neuroblastoma, we demonstrate how CLEAN can be used to gain novel mechanistic insights and identify putative drug targets in neuroblastoma.

cancer biology↗

bioRxiv2023

Benchmarking long-read sequencing strategies for obtaining ASV-resolved rRNA operons from environmental microeukaryotes

The use of short-read metabarcoding for classifying microeukaryotes is challenged by the lack of comprehensive 18S rRNA reference databases. While recent advances in high-throughput long-read sequencing provide the potential to greatly increase the phylogenetic coverage of these databases, the performance of different sequencing technologies and subsequent bioinformatics processing remain to be evaluated, primarily because of the absence of well-defined eukaryotic mock communities. To address this challenge, we created a eukaryotic rRNA operons clone-library and turned it into a precisely defined synthetic eukaryotic mock community. This mock community was then used to evaluate the performance of three long-read sequencing techniques (PacBio HiFi, and Nanopore UMI with/without clonal pre-amplification) and three tools for resolving amplicons sequence variants (ASVs) (Uchime3, Unoise3, and DADA2). We investigated the sensitivity of the sequencing techniques based on the number of detected mock taxa, and the accuracy of the different ASV-calling tools with a specific focus on the presence of chimera among the final rRNA operon ASVs. Based on our findings, we provide recommendations and best practice protocols for how to cost-effectively obtain essential error-free rRNA operons in high-throughput. An agricultural soil sample was used to demonstrate that the sequencing and bioinformatic results from the mock community also translates to highly diverse natural samples.

microbiology↗

bioRxiv2023

Skimming genomes for systematics and DNA barcodes of corals

1: Numerous genomic methods developed over the past two decades have enabled the discovery and extraction of orthologous loci to help resolve phylogenetic relationships across various taxa and scales. Genome skimming (or low-coverage whole genome sequencing) remains a low-cost, promising method to not only extract high-copy loci, but also 100s to 1000s of phylogenetically informative single-copy nuclear loci (e.g., ultraconserved elements [UCEs] and exons) from contemporary and historical museum samples. The subphylum Anthozoa, which includes important ecosystem engineers (e.g., stony corals, black corals, anemones and octocorals) in the marine environment, is in critical need of phylogenetic resolution and thus might benefit from a genome-skimming approach. 2: Genome skimming was conducted on 242 hexacorals and octocorals collected from 1890 to 2022. Using previously developed target-capture baitsets, we bioinformatically obtained UCEs and exons from the genome-skimming data and incorporated them with data from previously published target-capture studies. We also extracted partial to whole mitogenomes and nuclear rRNA genes from the skim data. 3: The mean number of UCE and exon loci extracted from the genome skimming data was 1,837 {+/-} 662 SD for octocorals and 1,422 {+/-} 720 loci for hexacorals; phylogenetic relationships were well resolved within each class. A mean of 1,422 {+/-} 720 loci were obtained from the historical museum specimens, with 1,253 loci recovered from the oldest specimen collected in 1886 and 1,336 loci recovered from a holotype. The nuclear rRNA genes and the majority of mitochondrial genes were successfully obtained from >95% of samples. Out of 99 circularized mitogenomes, 88% were recovered in samples from which we obtained >15M paired-end (PE) reads (>30M total reads); there was more variability in whether mitogenomes were circularized or not in samples with <15M PE reads. 4: Bioinformatically pulling UCEs, exons, mitochondrial genomes, and nuclear rRNA genes from genome skimming is a viable and low-cost option for phylogenetic studies. This approach can be used to review and support taxonomic revisions and reconstruct evolutionary histories, including historical museum and type specimens.

evolutionary biology↗

bioRxiv2023

Melatonin serves as a novel treatment in cystic fibrosis and inhibits cystic fibrosis through TGF-β1/Smad and EMT

BackgroundMelatonin (MEL) is an indole amine molecule primarily produced in the pineal gland. Melatonin has been shown in numerous studies to have anti-fibrosis characteristics in the kidney, liver, and other organs. However, it is still unclear how melatonin works in bladder fibrosis. We explored how melatonin affected animals with bladder fibrosis and its underlying mechanisms. Materials and MethodsMEL was used to treat human bladder smooth muscle cells (HBdSMCs) after they were stimulated with TGF-{beta}1 in vitro. Proteomic analysis and then bioinformatic analysis based on the alterations in these proteins were then performed on HBdSMCs from the different processing methods. To construct an in vivo bladder fibrosis model, we injected protamine sulfate (PS) and lipopolysaccharide (LPS) twice a week into the rat bladder for six weeks. After two weeks of PS/LPS treatment, the treatment group was treated with MEL (20mg/kg/d) for 4 weeks. Finally, we detected the expression of fibrosis markers from different perspectives. The TGF-{beta}1/Smad pathway, and EMT in cell and bladder tissues were also identified. Further proteomic analysis was also performed. ResultsIn the in vitro experiment, we found that TGF-{beta}1 treatment enhanced the fibrosis markers Collagen III and -SMA of HBdSMCs. E-cadherin expression decreased while TGF-{beta}1/Smad pathway was activated. Vimentin and N-cadherin expressions were also elevated at the same time. Similar findings were observed in the LPS group. After MEL treatment, the expression of collagen III and -SMA decreased, and the expression of E-cadherin increased, while the expression of Vimentin and N-cadherin also decreased. CCN1 and SQLE may be the important proteins in the development of bladder fibrosis, according to quantitative proteomics analysis. MEL can decrease their expressions which leadis to relief of bladder fibrosis. Bioinformatics analysis shows that the extracellular space structure related to metabolic pathways, actin filament binding, and stress fibers can serve as a pivotal focus in the management of fibrosis. ConclusionMelatonin attenuates bladder fibrosis by blocking the TGF-{beta}1/Smad pathway and EMT. CCN1 appears to be a possible therapeutic target for bladder fibrosis.

pharmacology and toxicology↗

bioRxiv2023

Prokrustean graph: An efficient data structure used to extract sequence information for arbitrary k-mer size ranges

The widespread adoption of k-mers in bioinformatics has led to efficient methods utilizing genomic sequences in a variety of biological tasks. However, understanding the influence of k-mer sizes within these methods remains a persistent challenge, as the outputs of complex bioinformatics pipelines obscure this influence with various noisy factors. The choice of k-mer size is often arbitrary, with justification frequently omitted in the literature and method tutorials. Furthermore, recent methods employing multiple k-mer sizes encounter significant computational challenges. Nevertheless, most methods are built on well-defined objects related to k-mers, such as de Bruijn graphs, Jaccard similarity, Bray-Curtis dissimilarity, and k-mer spectra. The role of k-mer sizes within these objects is more intuitive and can be described by numerous quantities and metrics. Therefore, exploring these objects across k-mer sizes opens opportunities for robust analyses and new applications. However, the evolution of k-mer objects with respect to k-mer sizes is surprisingly elusive. We introduce a novel substring index, the Prokrustean graph, that elucidates the transformation of k-mer sets across k-mer sizes. Our framework built upon this index rapidly computes k-mer-based quantities for all k-mer sizes, with computational complexity independent of the size range and dependent only on maximal repeats. For example, counting maximal simple paths in de Bruijn graphs for k = 1, ..., 100 is achieved in seconds using our index on a gigabase-scale dataset. We present a variety of such experiments relevant to pangenomics and metagenomics. The Prokrustean graph is space-efficiently constructed from the Burrows-Wheeler Transform. Through this construction, it becomes evident that other modern substring indices inherently face difficulties in exploring k-mer objects across sizes, which motivated our data structure. Our implementation is available at: https://github.com/KoslickiLab/prokrustean.

genetics↗

bioRxiv2023

Cross-Comparison of Gut Metagenomic Profiling Strategies

A critical issue in microbiome research is the selection of reliable laboratory and bioinformatics pipelines. In the absence of generally accepted technical benchmarks and evaluation standards, comparing data generated by different studies becomes challenging. In this work, we carried out the most comprehensive study to date on this topic. We encompassed every stage of processing, from DNA extraction to computational assessment. We adopted four procedures for DNA purification, six for library construction, three for sequencing, and five for bioinformatics. Additionally, we used datasets published by others to corroborate our results. We introduced a software tool that distinctively delivers consistent results, irrespective of sample or dataset origins. This study underscores the importance of methodological optimization at the outset of research projects to ensure the reliability of results and their comparability with findings from other studies. Additionally, this study provides an optimized robust pipeline for gut microbiome analysis.

microbiology↗

bioRxiv2023

Design and implementation of an asynchronous online course-based undergraduate research experience (CURE) in computational genomics

As genomics and information technologies advance, there is a growing demand for research scientists trained in bioinformatics methods to determine gene expression underlying cell biology in health and disease. One approach to increase the number of scientists proficient in bioinformatics is to expand access through online degree programs and remotely-accessible learning materials. Fully-online learners represent a significant and growing community of historically underrepresented students who are frequently excluded from research opportunities that require in-person attendance during standard operational hours. To address this opportunity gap, we developed an asynchronous course-based undergraduate research experience (CURE) for computational genomics specifically for fully-online biology students. We generated custom learning materials and leveraged remotely-accessible resources on a high performance computing cluster to address a novel research question: the effect of changing quality trimming parameters for RNA sequencing reads on the discovery of sex-based differential gene expression in the human placenta. Here we present the process by which the instructional team devised and distributed analysis to address this question over a 7.5-week CURE and provided students with concurrent training in biology, statistics, computer programming, and professional development integral to the successful execution of the project and future publications. Scores from identical learning assessments administered before and after completion of the CURE showed significant learning gains across biology and coding course objectives. Open-response progress reports were submitted weekly and identified self-reported adaptive coping strategies for challenges encountered throughout the course. The instruction team monitored the progress reports to identify problems that could be resolved through collaboration with instructors and peers via messaging platforms and virtual meetings. Analytics from the course messaging platform demonstrated that high posting engagement was strongly correlated to high normalized learning gains, showing that students can effectively use asynchronous communication platforms to facilitate learning. The online genomics CURE resulted in unanticipated positive outcomes, including students voluntarily extending their participation beyond the course duration, presenting their findings at research symposiums, and applying to graduate school. These outcomes underscore the effectiveness of this genomics CURE for training and recruitment purposes and demonstrate that students can be successful in online STEM-based research experiences if given channels for communication, bespoke and accessible learning materials, and the support of experts in the field. Online CUREs can provide valuable research experience to harness the potential of online STEM students towards a more skilled, diverse, and inclusive workforce for the advancement of biomedical science.

genomics↗

bioRxiv2023

Development and clinical validation of molecular subgrouping in medulloblastoma by targeted methylation sequencing

BackgroundThe WHO classification of CNS tumors confers promising prognostic value to the molecular classification of medulloblastoma (MB). Next-generation sequencing (NGS) has been the primary method employed for molecular classification through transcriptomic, genomic, or methylation profiling. However, due to cost and infrastructural needs, particularly in developing countries, we propose a relatively simple, rapid, and economical Sanger sequencing-based targeted methylation sequencing method for MB classification and prognostication. MethodsEleven epigenetic targets were amplified using optimized primers and bisulfite-converted DNA for Sanger sequencing. Chromas software was used for low-quality data trimming and NCBIs Needleman Wunsch alignment tool was used for sequence alignment to reference. The developed method was applied to tissues from twelve cases of medulloblastoma. ResultsSuccessful interpretation of methylation status in ten out of eleven targets was achieved which was sufficient for classification according to the latest WHO classification of Medulloblastoma tumors. Twelve medulloblastoma cases were classified into WNT (n=2), Group 3 (n=5), and Group 4 (n=5). ConclusionThe developed Sanger sequencing method is a cost-effective, in-house solution that can be used for molecular subgrouping of medulloblastoma. It offers an alternative to NGS, can be done on a case-to-case basis, and does not require high-end infrastructure, sample pooling, or extensive bioinformatics knowledge. Impact statementMolecular classification is imperative for determining the prognosis of medulloblastoma and is recommended by WHO. However, NGS proves to be an expensive option in developing countries. This study has come up with an affordable targeted methylation Sanger sequencing method requiring minimal bioinformatic skills, by utilizing epigenetic targets, for prognostication and risk stratification in medulloblastoma patients. The molecular subgroups of all recruited cases were successfully determined according to WHO classification which is crucial information that, when combined with clinical findings, will enable the clinicians to determine effective treatment strategies.

cancer biology↗

bioRxiv2023

Toward Best Practice in Identifying Subtle Differential Expression with RNA-seq: A Real-World Multi-Center Benchmarking Study Using Quartet and MAQC Reference Materials

Translating RNA-seq into clinical diagnostics requires ensuring the reliability of detecting clinically relevant subtle differential expressions, such as those between different disease subtypes or stages. Moreover, cross-laboratory reproducibility and consistency under diverse experimental and bioinformatics workflows urgently need to be addressed. As part of the Quartet project, we presented a comprehensive RNA-seq benchmarking study utilizing Quartet and MAQC RNA reference samples spiked with ERCC controls in 45 independent laboratories, each employing their in-house RNA-seq workflows. We assessed the data quality, accuracy and reproducibility of gene expression and differential gene expression and compared over 40 experimental processes and 140 combined differential analysis pipelines based on multiple ground truths. Here we show that real-world RNA-seq exhibited greater inter-laboratory variations when detecting subtle differential expressions between Quartet samples. Experimental factors including mRNA enrichment methods and strandedness, and each bioinformatics step, particularly normalization, emerged as primary sources of variations in gene expression and have a more pronounced impact on the subtle differential expression measurement. We underscored the pivotal role of experimental execution over the choice of experimental protocols, the importance of strategies for filtering low-expression genes, and optimal gene annotation and analysis tools. In summary, this study provided best practice recommendations for the development, optimization, and quality control of RNA-seq for clinical diagnostic purposes.

genomics↗

bioRxiv2023

Collaborative metabolic curation of an emerging model marine bacterium, Alteromonas macleodii ATCC 27126

Inferring the metabolic capabilities of an organism from its genome is a challenging process, relying on computationally-derived or manually curated metabolic networks. Manual curation can correct mistakes in the draft network and add missing reactions based on the literature, but requires significant expertise and is often the bottleneck for high-quality metabolic reconstructions. Here, we present a synopsis of a community curation workshop for the emerging model marine bacterium Alteromonas macleodii ATCC 27126 and its genome database in BioCyc, focusing on pathways for utilizing organic carbon and nitrogen sources. Due to the scarcity of biochemical information or gene knock-outs, the curation process relied primarily on published growth phenotypes and bioinformatic analyses, including comparisons with related Alteromonas strains. We report full pathways for the utilization of the algal polysaccharides alginate and pectin in contrast to inconclusive evidence for one carbon metabolism and mixed acid fermentation, in accordance with the lack of growth on methanol and formate. Pathways for amino acid degradation are ubiquitous across Alteromonas macleodii strains, yet enzymes in the pathways for the degradation of threonine, tryptophan and tyrosine were not identified. Nucleotide degradation pathways are also partial in ATCC 27126. We postulate that demonstrated growth on nitrate as sole N source proceeds via a nitrate reductase pathway that is a hybrid of known pathways. Our evidence highlights the value of joint and interactive curation efforts, but also shows major knowledge gaps regarding Alteromonas metabolism. The manually-curated metabolic reconstruction is available as a "Tier-2" database on BioCyc. ImportanceMetabolic reconstructions are vital for the systemic understanding of an organisms ecology. Here, we report the outcome of a collaborative, interactive curation workshop to build a curated "metabolic encyclopedia" for Alteromonas macleodii ATCC 27126, a marine heterotrophic bacterium with widespread occurrence. Curating pathways for polysaccharide degradation, one-carbon metabolism, and others closed major knowledge gaps, and identified further avenues of research. Our study highlights how the combination of bioinformatic, genomic and physiological evidence can be harvested into a detailed metabolic model, but also identifies challenges if little experimental data is available for support. Overall, we show how an interactive get-together by a diverse group of scientists can advance the ecological understanding of emerging model bacteria, with relevance for the entire scientific community.

microbiology↗

bioRxiv2023

Mapping Structural and Dynamic Divergence Across the MBOAT family

Membrane Bound O-acyltransferases (MBOATs) are membrane embedded enzymes which catalyse acyl chain transfer to a diverse group of substrates including lipids, small-molecules and proteins. Recent MBOAT structures reveal a conserved structural core, despite wide-ranging functional specificity across both prokaryotes and eukaryotes. The structural basis of catalytic specificity, regulation and interactions with the surrounding environment remain uncertain, hindering effective therapeutic targeting. Here, we combine comparative molecular dynamics (MD) simulations with bioinformatics to assess molecular and interactional divergence across the family. In simulations, MBOATs differentially distort the bilayer depending on their substrate type. Additionally, we identify specific lipid binding sites surrounding MBOAT reactant gates into the surrounding membrane. We use bioinformatics to reveal a conserved role for re-entrant loop-2 in stabilisation of the MBOAT fold and identify a key hydrogen bond involved in DGAT1 dimerisation. Finally, we predict differences in MBOAT core solvation and water gating properties across the family. These data are pertinent to the design of MBOAT specific inhibitors that encompass dynamic information within cellular mimetic environments.

biochemistry↗

bioRxiv2024

Genome binding properties of Zic transcription factors underlie their changing functions during neuronal maturation

BackgroundThe Zic family of transcription factors (TFs) promote both proliferation and maturation of cerebellar granule neurons (CGNs), raising the question of how a single, constitutively expressed TF family can support distinct developmental processes. Here we use an integrative experimental and bioinformatic approach to discover the regulatory relationship between Zic TF binding and changing programs of gene transcription during CGN differentiation. ResultsWe first established a bioinformatic pipeline to integrate Zic ChIP-seq data from the developing mouse cerebellum with other genomic datasets from the same tissue. In newborn CGNs, Zic TF binding predominates at active enhancers that are co-bound by developmentally-regulated TFs including Atoh1, whereas in mature CGNs, Zic TF binding consolidates toward promoters where it co-localizes with activity-regulated TFs. We then performed CUT&RUN-seq in differentiating CGNs to define both the time course of developmental shifts in Zic TF binding and their relationship to gene expression. Mapping Zic TF binding sites to genes using chromatin looping, we identified the set of Zic target genes that have altered expression in RNA-seq from Zic1 or Zic2 knockdown CGNs. ConclusionOur data show that Zic TFs are required for both induction and repression of distinct, developmentally regulated target genes through a mechanism that is largely independent of changes in Zic TF binding. We suggest that the differential collaboration of Zic TFs with other TF families underlies the shift in their biological functions across CGN development.

neuroscience↗