Cell Rep Methods. 2023 Oct 23;3(10):100619. doi: 10.1016/j.crmeth.2023.100619.

ABSTRACT

High-dimensional flow cytometry is the gold standard to study the human immune system in large cohorts. However, large sample sizes increase inter-experimental variation because of technical and experimental inaccuracies introduced by batch variability. Our high-throughput sample processing pipeline in combination with 28-color flow cytometry focuses on increased throughput (192 samples/experiment) and high reproducibility. We implemented quality control checkpoints to reduce technical and experimental variation. Finally, we integrated FlowSOM clustering to facilitate automated data analysis and demonstrate the reproducibility of our pipeline in a study with 3,357 samples. We reveal age-associated immune dynamics in 2,300 individuals, signified by decreasing T and B cell subsets with age. In addition, by combining genetic analyses, our approach revealed unique immune signatures associated with a single nucleotide polymorphism (SNP) that abrogates CD45 isoform splicing. In summary, we provide a versatile and reliable high-throughput, flow cytometry-based pipeline for immune discovery and exploration in large cohorts.

PMID:37883924 | DOI:10.1016/j.crmeth.2023.100619

PLoS Comput Biol. 2023 Oct 26;19(10):e1011576. doi: 10.1371/journal.pcbi.1011576. Online ahead of print.

ABSTRACT

Long-read RNA sequencing has arisen as a counterpart to short-read sequencing, with the potential to capture full-length isoforms, albeit at the cost of lower depth. Yet this potential is not fully realized due to inherent limitations of current long-read assembly methods and underdeveloped approaches to integrate short-read data. Here, we critically compare the existing methods and develop a new integrative approach to characterize a particularly challenging pool of low-abundance long noncoding RNA (lncRNA) transcripts from short- and long-read sequencing in two distinct cell lines. Our analysis reveals severe limitations in each of the sequencing platforms. For short-read assemblies, coverage declines at transcript termini resulting in ambiguous ends, and uneven low coverage results in segmentation of a single transcript into multiple transcripts. Conversely, long-read sequencing libraries lack depth and strand-of-origin information in cDNA-based methods, culminating in erroneous assembly and quantitation of transcripts. We also discover a cDNA synthesis artifact in long-read datasets that markedly impacts the identity and quantitation of assembled transcripts. Towards remediating these problems, we develop a computational pipeline to "strand" long-read cDNA libraries that rectifies inaccurate mapping and assembly of long-read transcripts. Leveraging the strengths of each platform and our computational stranding, we also present and benchmark a hybrid assembly approach that drastically increases the sensitivity and accuracy of full-length transcript assembly on the correct strand and improves detection of biological features of the transcriptome. When applied to a challenging set of under-annotated and cell-type variable lncRNA, our method resolves the segmentation problem of short-read sequencing and the depth problem of long-read sequencing, resulting in the assembly of coherent transcripts with precise 5' and 3' ends. Our workflow can be applied to existing datasets for superior demarcation of transcript ends and refined isoform structure, which can enable better differential gene expression analyses and molecular manipulations of transcripts.

PMID:37883581 | DOI:10.1371/journal.pcbi.1011576

Elife. 2023 Oct 26;12:RP87958. doi: 10.7554/eLife.87958.

ABSTRACT

Catalytic signaling outputs of protein kinases are dynamically regulated by an array of structural mechanisms, including allosteric interactions mediated by intrinsically disordered segments flanking the conserved catalytic domain. The doublecortin-like kinases (DCLKs) are a family of microtubule-associated proteins characterized by a flexible C-terminal autoregulatory 'tail' segment that varies in length across the various human DCLK isoforms. However, the mechanism whereby these isoform-specific variations contribute to unique modes of autoregulation is not well understood. Here, we employ a combination of statistical sequence analysis, molecular dynamics simulations, and in vitro mutational analysis to define hallmarks of DCLK family evolutionary divergence, including analysis of splice variants within the DCLK1 sub-family, which arise through alternative codon usage and serve to 'supercharge' the inhibitory potential of the DCLK1 C-tail. We identify co-conserved motifs that readily distinguish DCLKs from all other calcium calmodulin kinases (CAMKs), and a 'Swiss Army' assembly of distinct motifs that tether the C-terminal tail to conserved ATP and substrate-binding regions of the catalytic domain to generate a scaffold for autoregulation through C-tail dynamics. Consistently, deletions and mutations that alter C-terminal tail length or interfere with co-conserved interactions within the catalytic domain alter intrinsic protein stability, nucleotide/inhibitor binding, and catalytic activity, suggesting isoform-specific regulation of activity through alternative splicing. Our studies provide a detailed framework for investigating kinome-wide regulation of catalytic output through cis-regulatory events mediated by intrinsically disordered segments, opening new avenues for the design of mechanistically divergent DCLK1 modulators, stabilizers, or degraders.

PMID:37883155 | DOI:10.7554/eLife.87958

Bioinformatics. 2023 Oct 26:btad658. doi: 10.1093/bioinformatics/btad658. Online ahead of print.

ABSTRACT

MOTIVATION: Annotations of biochemical models provide details of chemical species, documentation of chemical reactions, and other essential information. Unfortunately, the vast majority of biochemical models have few, if any, annotations, or the annotations provide insufficient detail to understand the limitations of the model. The quality and quantity of annotations can be improved by developing tools that recommend annotations. For example, recommender tools have been developed for annotations of genes. Although annotating genes is conceptually similar to annotating biochemical models, there are important technical differences that make it difficult to directly apply this prior work.

RESULTS: We present AMAS, a system that predicts annotations for elements of models represented in the Systems Biology Markup Language (SBML) community standard. We provide a general framework for predicting model annotations for a query element based on a database of annotated reference elements and a match score function that calculates the similarity between the query element and reference elements. The framework is instantiated to specific element types (e.g., species, reactions) by specifying the reference database (e.g., ChEBI for species) and the match score function (e.g., string similarity). We analyze the computational efficiency and prediction quality of AMAS for species and reactions in BiGG and BioModels and find that it has sub-second response times and accuracy between 80% and 95% depending on specifics of what is predicted. We have incorporated AMAS into an open-source, pip-installable Python package that can run as a command-line tool that predicts and adds annotations to species and reactions to an SBML model.

AVAILABILITY: Our project is hosted at https://github.com/sys-bio/AMAS, where we provide examples, documentation, and source code files. Our source code is licensed under the MIT open-source license.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37882737 | DOI:10.1093/bioinformatics/btad658

mBio. 2023 Oct 26:e0171823. doi: 10.1128/mbio.01718-23. Online ahead of print.

ABSTRACT

Plasmodium parasites rely on a functional electron transport chain (ETC) within their mitochondrion for proliferation, and compounds targeting mitochondrial functions are validated antimalarials. Here, we localize Plasmodium falciparum patatin-like phospholipase 2 (PfPNPLA2, PF3D7_1358000) to the mitochondrion and reveal that disruption of the PfPNPLA2 gene impairs asexual replication. PfPNPLA2-null parasites are hypersensitive to proguanil and inhibitors of the mitochondrial ETC, including atovaquone. In addition, PfPNPLA2-deficient parasites show reduced mitochondrial respiration and reduced mitochondrial membrane potential, indicating that disruption of PfPNPLA2 leads to a defect in the parasite ETC. Lipidomic analysis of the mitochondrial phospholipid cardiolipin (CL) reveals that loss of PfPNPLA2 is associated with a moderate shift toward shorter-chained and more saturated CL species, implying a contribution of PfPNPLA2 to CL remodeling. PfPNPLA2-deficient parasites display profound defects in gametocytogenesis, underlining the importance of a functional mitochondrial ETC during both the asexual and sexual development of the parasite. IMPORTANCE For their proliferation within red blood cells, malaria parasites depend on a functional electron transport chain (ETC) within their mitochondrion, which is the target of several antimalarial drugs. Here, we have used gene disruption to identify a patatin-like phospholipase, PfPNPLA2, as important for parasite replication and mitochondrial function in Plasmodium falciparum. Parasites lacking PfPNPLA2 show defects in their ETC and become hypersensitive to mitochondrion-targeting drugs. Furthermore, PfPNPLA2-deficient parasites show differences in the composition of their cardiolipins, a unique class of phospholipids with key roles in mitochondrial functions. Finally, we demonstrate that parasites devoid of PfPNPLA2 have a defect in gametocyte maturation, underlining the importance of a functional ETC for parasite transmission to the mosquito vector.

PMID:37882543 | DOI:10.1128/mbio.01718-23

New Phytol. 2023 Oct 25. doi: 10.1111/nph.19353. Online ahead of print.

ABSTRACT

Legume nodulation requires light perception by plant shoots and precise long-distance communication between shoot and root. Recent studies have revealed that TGACG-motif binding factors (GmSTFs) integrate light signals to promote root nodulation; however, the regulatory mechanisms underlying nodule formation in changing light conditions remain elusive. Here, we applied genetic engineering, metabolite measurement, and transcriptional analysis to study soybean (Glycine max) nodules. We clarify a fine-tuning mechanism in response to ultraviolet B (UV-B) irradiation and rhizobia infection, involving GmUVR8-dependent UV-B perception and GmSTF3/4-GmMYB12-GmCHS-mediated (iso)flavonoid biosynthesis for soybean nodule formation. GmUVR8 receptor-perceived UV-B signal triggered R2R3-MYB transcription factors GmMYB12-dependent flavonoid biosynthesis separately in shoot and root. In shoot, UV-B-triggered flavonoid biosynthesis relied on GmUVR8a, b, c receptor-dependent activation of GmMYB12L-GmCHS8 (chalcone synthase) module. In root, UV-B signaling distinctly promotes the accumulation of the isoflavones, daidzein, and its derivative coumestrol, via GmMYB12B2-GmCHS9 module, resulting in hypernodulation. The mobile transcription factors, GmSTF3/4, bind to cis-regulatory elements in the GmMYB12L, GmMYB12B2, and GmCHS9 promoters, to coordinate UV-B light perception in shoot and (iso)flavonoid biosynthesis in root. Our findings establish a novel shoot-to-root communication module involved in soybean nodulation and reveal an adaptive strategy employed by soybean roots in response to UV-B light.

PMID:37881032 | DOI:10.1111/nph.19353

Dev Biol. 2023 Oct 23:S0012-1606(23)00168-9. doi: 10.1016/j.ydbio.2023.09.014. Online ahead of print.

ABSTRACT

The orphan nuclear receptor Tailless (Tll) exhibits conserved roles in brain formation and maintenance that are shared, for example, with vertebrate orthologous forms (Tlx). However, the early expression of tll in two gap domains in the segmentation cascade of Drosophila is unusual even for most other insects. Here we investigate tll regulation on pair-rule stripes. With ectopic misexpression of tll we detected unexpected repression of almost all pair-rule stripes of hairy (h), even-skipped (eve), runt (run), and fushi-tarazu (ftz). Examining Tll embryonic ChIP-chip data with regions mapped as Cis-Regulatory Modules (CRMs) of pair-rule stripes we verified Tll interactions to these regions. With the ChIP-chip data we also verified Tll interactions to the CRMs of gap domains and in the misexpression assay, Tll-mediated repression on Kruppel (Kr), kni (kni) and giant (gt) according to their differential sensitivity to Tll. These results with gap genes confirmed previous data from the literature and argue against indirect repression roles of Tll in the striped pattern. Moreover, the prediction of Tll binding sites in the CRMs of eve stripes and the mathematical modeling of their removal using an experimentally validated theoretical framework shows effects on eve stripes compatible with the absence of a repressor binding to the CRMs. In addition, modeling increased tll levels in the embryo results in the differential repression of eve stripes, agreeing well with the results of the misexpression assay. In genetic assays we investigated eve 5, that is strongly repressed by the ectopic domain and representative of more central stripes not previously implied to be under direct regulation of tll. While this stripe is little affected in tll-, its posterior border is expanded in gt- but detected with even greater expansion in gt-;tll-. We end up by discussing tll with key roles in combinatorial repression mechanisms to contain the expression of medial patterns of the segmentation cascade in the extremities of the embryo.

PMID:37879494 | DOI:10.1016/j.ydbio.2023.09.014

Nature. 2023 Oct 25. doi: 10.1038/s41586-023-06676-3. Online ahead of print.

ABSTRACT

Identifying metabolic steps that are specifically required for the survival of cancer cells but are dispensable in normal cells remains a challenge1. Here we report a therapeutic vulnerability in a sugar nucleotide biosynthetic pathway that can be exploited in cancer cells with only a limited impact on normal cells. A systematic examination of conditionally essential metabolic enzymes revealed that UXS1, a Golgi enzyme that converts one sugar nucleotide (UDP-glucuronic acid, UDPGA) to another (UDP-xylose), is essential only in cells that express high levels of the enzyme immediately upstream of it, UGDH. This conditional relationship exists because UXS1 is required to prevent excess accumulation of UDPGA, which is produced by UGDH. UXS1 not only clears away UDPGA but also limits its production through negative feedback on UGDH. Excess UDPGA disrupts Golgi morphology and function, which impedes the trafficking of surface receptors such as EGFR to the plasma membrane and diminishes the signalling capacity of cells. UGDH expression is elevated in several cancers, including lung adenocarcinoma, and is further enhanced during chemoresistant selection. As a result, these cancer cells are selectively dependent on UXS1 for UDPGA detoxification, revealing a potential weakness in tumours with high levels of UGDH.

PMID:37880368 | DOI:10.1038/s41586-023-06676-3

Trends Endocrinol Metab. 2023 Oct 23:S1043-2760(23)00216-3. doi: 10.1016/j.tem.2023.10.003. Online ahead of print.

ABSTRACT

Parsing the intricate interplay between gut microbiota, gene modulation, and host metabolism remains challenging. Wang et al. employed diverse methods to uncover how the gut microbiota reshapes intestinal lipid metabolism through the lncRNA Snhg9, underscoring the value of systems biology approaches in dissecting host-microbiome relationships involved in metabolic disorders.

PMID:37880053 | DOI:10.1016/j.tem.2023.10.003

Plant Physiol. 2023 Oct 25:kiad572. doi: 10.1093/plphys/kiad572. Online ahead of print.

ABSTRACT

Arabidopsis (Arabidopsis thaliana) ecotype Col-0 has plastid and mitochondrial genomes encoding over 100 proteins. Public databases (e.g., Araport11) have redundancy and discrepancies in gene identifiers for these organelle-encoded proteins. RNA editing results in changes to specific amino acid residues or creation of start and stop codons for many of these proteins, but the impact of RNA editing at the protein level is largely unexplored due to the complexities of detection. Here, we assembled the non-redundant set of identifiers, their correct protein sequences, and 452 predicted non-synonymous editing sites of which 56 are edited at lower frequency. We then determined accumulation of edited and/or unedited proteoforms by searching ∼259 million raw tandem mass spectrometry spectra from ProteomeXchange, which is part of PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/). We identified all mitochondrial proteins and all except three plastid-encoded proteins (NdhG/Ndh6, PsbM, Rps16), but no proteins predicted from the four open reading frames were identified. We suggest that Rps16 and three of the open reading frames are pseudogenes. Detection frequencies for each edit site and type of edit (e.g., S to L/F) were determined at the protein level, cross-referenced against the metadata (e.g., tissue), and evaluated for technical detection challenges. We detected 167 predicted edit sites at the proteome level. Minor frequency sites were edited at low frequency at the protein level except for cytochrome C biogenesis 382 at residue 124 (Ccb382-124) Major frequency sites (>50% editing of RNA) only accumulated in edited form (>98-100% edited) at the protein level, with the exception of Rpl5-22. We conclude that RNA editing for major editing sites is required for stable protein accumulation.

PMID:37879112 | DOI:10.1093/plphys/kiad572

Proc Natl Acad Sci U S A. 2023 Oct 31;120(44):e2304302120. doi: 10.1073/pnas.2304302120. Epub 2023 Oct 25.

ABSTRACT

The AlphaFold Protein Structure Database contains predicted structures for millions of proteins. For the majority of human proteins that contain intrinsically disordered regions (IDRs), which do not adopt a stable structure, it is generally assumed that these regions have low AlphaFold2 confidence scores that reflect low-confidence structural predictions. Here, we show that AlphaFold2 assigns confident structures to nearly 15% of human IDRs. By comparison to experimental NMR data for a subset of IDRs that are known to conditionally fold (i.e., upon binding or under other specific conditions), we find that AlphaFold2 often predicts the structure of the conditionally folded state. Based on databases of IDRs that are known to conditionally fold, we estimate that AlphaFold2 can identify conditionally folding IDRs at a precision as high as 88% at a 10% false positive rate, which is remarkable considering that conditionally folded IDR structures were minimally represented in its training data. We find that human disease mutations are nearly fivefold enriched in conditionally folded IDRs over IDRs in general and that up to 80% of IDRs in prokaryotes are predicted to conditionally fold, compared to less than 20% of eukaryotic IDRs. These results indicate that a large majority of IDRs in the proteomes of human and other eukaryotes function in the absence of conditional folding, but the regions that do acquire folds are more sensitive to mutations. We emphasize that the AlphaFold2 predictions do not reveal functionally relevant structural plasticity within IDRs and cannot offer realistic ensemble representations of conditionally folded IDRs.

PMID:37878721 | DOI:10.1073/pnas.2304302120

PLoS One. 2023 Oct 25;18(10):e0292879. doi: 10.1371/journal.pone.0292879. eCollection 2023.

ABSTRACT

Next generation sequencing of circulating tumor DNA (ctDNA) has been used as a noninvasive alternative for cancer diagnosis and characterization of tumor mutational landscape. However, low ctDNA fraction and other factors can limit the ability of ctDNA analysis to capture tumor-specific and actionable variants. In this study, whole-exome sequencings (WES) were performed on paired ctDNA and tumor biopsy in 15 cancer patients to assess the extent of concordance between mutational profiles derived from the two source materials. We found that up to 16.4% ctDNA fraction can still be insufficient for detecting tumor-specific variants and that good concordance with tumor biopsy is consistently achieved at higher ctDNA fractions. Most importantly, ctDNA analysis can consistently capture tumor heterogeneity and detect key cancer-related genes even in a patient with both primary and metastatic tumors.

PMID:37878600 | DOI:10.1371/journal.pone.0292879

ACS Appl Mater Interfaces. 2023 Oct 25. doi: 10.1021/acsami.3c08819. Online ahead of print.

ABSTRACT

The coronavirus disease 2019 (COVID-19) epidemic has given a warning that it is important to explore the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in clinical specimens or environmental samples for public health strategies and future variants. The surface-enhanced Raman spectroscopy (SERS) technique was demonstrated to achieve this goal. However, the consistency of signals originating from the poor compatibility of virions with SERS hotspots remains a key scientific challenge for the practical applications of SERS. Herein, we develop a SERS platform for the ultrasensitive and rapid detection of SARS-CoV-2 antigen within 20 min by the combination of a highly consistent SERS substrate and a supervised deep learning algorithm. A V-shaped resonant cavity array (VRC) substrate was fabricated to trap SARS-CoV-2 virions in the periodic V cavity array and stimulate the integral SERS signal of the virus via a resonance coupling effect. Benefiting from the unique architecture of the VRC substrate, we were able to directly detect the SARS-CoV-2 virus with high sensitivity and high consistency. These excellent performances enabled us to identify five different kinds of SARS-CoV-2 variants and detect SARS-CoV-2 from clinical and environmental samples with high accuracies.

PMID:37878252 | DOI:10.1021/acsami.3c08819

J Exp Bot. 2023 Oct 25:erad405. doi: 10.1093/jxb/erad405. Online ahead of print.

ABSTRACT

High temperatures impair plant and algal growth and reduce food and biofuel production, but the underlying mechanisms remain elusive. The unicellular green alga Chlamydomonas reinhardtii is a superior model to study heat responses in photosynthetic cells due to its fast growth rate, many similarities in cellular processes to land plants, simple and sequenced genome, and ample genetic and genomics resources. Chlamydomonas grows in light by photosynthesis and/or with the externally supplied organic carbon source, acetate. Most of the published research about Chlamydomonas heat responses used acetate-containing medium. Understanding how organic carbon sources affect heat responses is important for the algal industry but understudied. We cultivated Chlamydomonas wild-type cultures under highly controlled conditions in photobioreactors at control of 25oC, moderate high temperature of 35oC, or acute high temperature of 40oC with and without constant acetate supply for 1- or 4-days. Our results showed that 35oC increased algal growth with constant acetate supply but reduced algal growth without sufficient acetate. The overlooked and dynamic effects of 35oC could be explained by induced carbon metabolism, including acetate uptake and assimilation, glyoxylate cycle, gluconeogenesis pathways, and glycolysis. Acute high temperature at 40oC for more than 2 days was lethal to algal cultures with and without constant acetate supply. Our research provides insights to understand algal heat responses and help improve thermotolerance in photosynthetic cells.

PMID:37877811 | DOI:10.1093/jxb/erad405

EMBO Rep. 2023 Oct 25:e57849. doi: 10.15252/embr.202357849. Online ahead of print.

ABSTRACT

Oxygen is essential for viability in mammalian organisms. However, cells are often exposed to changes in oxygen availability, due to either increased demand or reduced oxygen supply, herein called hypoxia. To be able to survive and/or adapt to hypoxia, cells activate a variety of signalling cascades resulting in changes to chromatin, gene expression, metabolism and viability. Cellular signalling is often mediated via post-translational modifications (PTMs), and this is no different in response to hypoxia. Many enzymes require oxygen for their activity and oxygen can directly influence several PTMS. Here, we review the direct impact of changes in oxygen availability on PTMs such as proline, asparagine, histidine and lysine hydroxylation, lysine and arginine methylation and cysteine dioxygenation, with a focus on mammalian systems. In addition, indirect hypoxia-dependent effects on phosphorylation, ubiquitination and sumoylation will also be discussed. Direct and indirect oxygen-regulated changes to PTMs are coordinated to achieve the cell's ultimate response to hypoxia. However, specific oxygen sensitivity and the functional relevance of some of the identified PTMs still require significant research.

PMID:37877678 | DOI:10.15252/embr.202357849

J Proteome Res. 2023 Oct 25. doi: 10.1021/acs.jproteome.3c00295. Online ahead of print.

ABSTRACT

Leptospirosis, a remerging zoonosis, has no effective vaccine or an unambiguous early diagnostic reagent. Proteins differentially expressed (DE) under pathogenic conditions will be useful candidates for antileptospiral measures. We employed a multipronged approach comprising high-resolution TMT-labeled LC-MS/MS-based proteome analysis coupled with bioinformatics on leptospiral proteins following Triton X-114 subcellular fractionation of leptospires treated under physiological temperature and osmolarity that mimic infection. Although there were significant changes in the DE proteins at the level of the entire cell, there were notable changes in proteins at the subcellular level, particularly on the outer membrane (OM), that show the significance of subcellular proteome analysis. The detergent-enriched proteins, representing outer membrane proteins (OMPs), exhibited a dynamic nature and upregulation under various physiological conditions. It was found that pathogenic proteins showed a higher proportion of upregulation compared to the nonpathogenic proteins in the OM. Further analysis identified 17 virulent proteins exclusively upregulated in the outer membrane during infection that could be useful for vaccine and diagnostic targets. The DE proteins may aid in metabolic adaptation and are enriched in pathways related to signal transduction and antibiotic biosynthesis. Many upregulated proteins belong to protein export systems such as SEC translocase, T2SSs, and T1SSs, indicating their sequential participation in protein transport to the outer leaflet of the OM. Further studies on OM-localized proteins may shed light on the pathogenesis of leptospirosis and serve as the basis for effective countermeasures.

PMID:37877620 | DOI:10.1021/acs.jproteome.3c00295

Front Mol Biosci. 2023 Oct 9;10:1274463. doi: 10.3389/fmolb.2023.1274463. eCollection 2023.

ABSTRACT

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals' health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the molecular mechanisms underlying the association between MUO and COVID-19 are poorly understood. Methods: We sought to reveal the relationship between MUO and COVID-19 using bioinformatics and systems biology analysis approaches. Here, two datasets (GSE196822 and GSE152991) were employed to extract differentially expressed genes (DEGs) to identify common hub genes, shared pathways, transcriptional regulatory networks, gene-disease relationship and candidate drugs. Results: Based on the identified 65 common DEGs, the complement-related pathways and neutrophil degranulation-related functions are found to be mainly affected. The hub genes, which included SPI1, CD163, C1QB, SIGLEC1, C1QA, ITGAM, CD14, FCGR1A, VSIG4 and C1QC, were identified. From the interaction network analysis, 65 transcription factors (TFs) were found to be the regulatory signals. Some infections, inflammation and liver diseases were found to be most coordinated with the hub genes. Importantly, Paricalcitol, 3,3',4,4',5-Pentachlorobiphenyl, PD 98059, Medroxyprogesterone acetate, Dexamethasone and Tretinoin HL60 UP have shown possibility as therapeutic agents against COVID-19 and MUO. Conclusion: This study provides new clues and references to treat both COVID-19 and MUO.

PMID:37877121 | PMC:PMC10591333 | DOI:10.3389/fmolb.2023.1274463

Comput Struct Biotechnol J. 2023 Oct 5;21:4960-4973. doi: 10.1016/j.csbj.2023.10.002. eCollection 2023.

ABSTRACT

The accurate prediction of phenotypes in microorganisms is a main challenge for systems biology. Genome-scale models (GEMs) are a widely used mathematical formalism for predicting metabolic fluxes using constraint-based modeling methods such as flux balance analysis (FBA). However, they require prior knowledge of the metabolic network of an organism and appropriate objective functions, often hampering the prediction of metabolic fluxes under different conditions. Moreover, the integration of omics data to improve the accuracy of phenotype predictions in different physiological states is still in its infancy. Here, we present a novel approach for predicting fluxes under various conditions. We explore the use of supervised machine learning (ML) models using transcriptomics and/or proteomics data and compare their performance against the standard parsimonious FBA (pFBA) approach using case studies of Escherichia coli organism as an example. Our results show that the proposed omics-based ML approach is promising to predict both internal and external metabolic fluxes with smaller prediction errors in comparison to the pFBA approach. The code, data, and detailed results are available at the project's repository[1].

PMID:37876626 | PMC:PMC10590844 | DOI:10.1016/j.csbj.2023.10.002

J R Soc Interface. 2023 Oct;20(207):20230505. doi: 10.1098/rsif.2023.0505. Epub 2023 Oct 25.

ABSTRACT

This paper addresses two topics in systems biology, the hypothesis that biological systems are modular and the problem of relating structure and function of biological systems. The focus here is on gene regulatory networks, represented by Boolean network models, a commonly used tool. Most of the research on gene regulatory network modularity has focused on network structure, typically represented through either directed or undirected graphs. But since gene regulation is a highly dynamic process as it determines the function of cells over time, it is natural to consider functional modularity as well. One of the main results is that the structural decomposition of a network into modules induces an analogous decomposition of the dynamic structure, exhibiting a strong relationship between network structure and function. An extensive simulation study provides evidence for the hypothesis that modularity might have evolved to increase phenotypic complexity while maintaining maximal dynamic robustness to external perturbations.

PMID:37876275 | DOI:10.1098/rsif.2023.0505

Proteins. 2023 Oct 24. doi: 10.1002/prot.26602. Online ahead of print.

ABSTRACT

The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty-two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and x-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as noncanonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.

PMID:37876231 | DOI:10.1002/prot.26602