Front Endocrinol (Lausanne). 2023 Mar 17;14:1049708. doi: 10.3389/fendo.2023.1049708. eCollection 2023.

ABSTRACT

INTRODUCTION: Polybrominated diphenyl ethers (PBDEs) are commercially used flame retardants that bioaccumulate in human tissues, including breast milk. PBDEs produce endocrine and metabolic disruption in experimental animals and have been associated with diabetes and metabolic syndrome (MetS) in humans, however, their sex-specific diabetogenic effects are not completely understood. Our past works show glucolipid dysregulation resulting from perinatal exposure to the commercial penta-mixture of PBDEs, DE-71, in C57BL/6 female mice.

METHODS: As a comparison, in the current study, the effects of DE-71 on glucose homeostasis in male offspring was examined. C57BL/6N dams were exposed to DE-71 at 0.1 mg/kg/d (L-DE-71), 0.4 mg/kg/d (H-DE-71), or received corn oil vehicle (VEH/CON) for a total of 10 wks, including gestation and lactation and their male offspring were examined in adulthood.

RESULTS: Compared to VEH/CON, DE-71 exposure produced hypoglycemia after a 11 h fast (H-DE-71). An increased fast duration from 9 to 11 h resulted in lower blood glucose in both DE-71 exposure groups. In vivo glucose challenge showed marked glucose intolerance (H-DE-71) and incomplete clearance (L- and H-DE-71). Moreover, L-DE-71-exposed mice showed altered glucose responses to exogenous insulin, including incomplete glucose clearance and/or utilization. In addition, L-DE-71 produced elevated levels of plasma glucagon and the incretin, active glucagon-like peptide-1 (7-36) amide (GLP-1) but no changes were detected in insulin. These alterations, which represent criteria used clinically to diagnose diabetes in humans, were accompanied with reduced hepatic glutamate dehydrogenase enzymatic activity, elevated adrenal epinephrine and decreased thermogenic brown adipose tissue (BAT) mass, indicating involvement of several organ system targets of PBDEs. Liver levels of several endocannabinoid species were not altered.

DISCUSSION: Our findings demonstrate that chronic, low-level exposure to PBDEs in dams can dysregulate glucose homeostasis and glucoregulatory hormones in their male offspring. Previous findings using female siblings show altered glucose homeostasis that aligned with a contrasting diabetogenic phenotype, while their mothers displayed more subtle glucoregulatory alterations, suggesting that developing organisms are more susceptible to DE-71. We summarize the results of the current work, generated in males, considering previous findings in females. Collectively, these findings offer a comprehensive account of differential effects of environmentally relevant PBDEs on glucose homeostasis and glucoregulatory endocrine dysregulation of developmentally exposed male and female mice.

PMID:37008952 | PMC:PMC10063979 | DOI:10.3389/fendo.2023.1049708

Health Inf Sci Syst. 2023 Mar 29;11(1):18. doi: 10.1007/s13755-023-00218-x. eCollection 2023 Dec.

ABSTRACT

Chronic metabolic diseases arise from changes in metabolic fluxes through biomolecular pathways and gene networks accumulated over the lifetime of an individual. While clinical and biochemical profiles present just real-time snapshots of the patients' health, efficient computation models of the pathological disturbance of biomolecular processes are required to achieve individualized mechanistic insights into disease progression. Here, we describe the Generalized metabolic flux analysis (GMFA) for addressing this gap. Suitably grouping individual metabolites/fluxes into pools simplifies the analysis of the resulting more coarse-grain network. We also map non-metabolic clinical modalities onto the network with additional edges. Instead of using the time coordinate, the system status (metabolite concentrations and fluxes) is quantified as function of a generalized extent variable (a coordinate in the space of generalized metabolites) that represents the system's coordinate along its evolution path and evaluates the degree of change between any two states on that path. We applied GMFA to analyze Type 2 Diabetes Mellitus (T2DM) patients from two cohorts: EVAS (289 patients from Singapore) and NHANES (517) from the USA. Personalized systems biology models (digital twins) were constructed. We deduced disease dynamics from the individually parameterized metabolic network and predicted the evolution path of the metabolic health state. For each patient, we obtained an individual description of disease dynamics and predict an evolution path of the metabolic health state. Our predictive models achieve an ROC-AUC in the range 0.79-0.95 (sensitivity 80-92%, specificity 62-94%) in identifying phenotypes at the baseline and predicting future development of diabetic retinopathy and cataract progression among T2DM patients within 3 years from the baseline. The GMFA method is a step towards realizing the ultimate goal to develop practical predictive computational models for diagnostics based on systems biology. This tool has potential use in chronic disease management in medical practice.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13755-023-00218-x.

PMID:37008895 | PMC:PMC10060506 | DOI:10.1007/s13755-023-00218-x

Front Plant Sci. 2023 Mar 16;14:1154088. doi: 10.3389/fpls.2023.1154088. eCollection 2023.

ABSTRACT

Roots are sensors evolved to simultaneously respond to manifold signals, which allow the plant to survive. Root growth responses, including the modulation of directional root growth, were shown to be differently regulated when the root is exposed to a combination of exogenous stimuli compared to an individual stress trigger. Several studies pointed especially to the impact of the negative phototropic response of roots, which interferes with the adaptation of directional root growth upon additional gravitropic, halotropic or mechanical triggers. This review will provide a general overview of known cellular, molecular and signalling mechanisms involved in directional root growth regulation upon exogenous stimuli. Furthermore, we summarise recent experimental approaches to dissect which root growth responses are regulated upon which individual trigger. Finally, we provide a general overview of how to implement the knowledge gained to improve plant breeding.

PMID:37008498 | PMC:PMC10060999 | DOI:10.3389/fpls.2023.1154088

Front Plant Sci. 2023 Mar 17;14:1143512. doi: 10.3389/fpls.2023.1143512. eCollection 2023.

ABSTRACT

Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs.

PMID:37008459 | PMC:PMC10063887 | DOI:10.3389/fpls.2023.1143512

Nanoethics. 2023;17(1):1. doi: 10.1007/s11569-023-00436-3. Epub 2023 Mar 28.

ABSTRACT

With the advent of synthetic biology, scientists are increasingly relying on digital sequence information, instead of physical genetic resources. This article examines the potential impact of this shift on the access and benefit-sharing (ABS) regime of the Convention on Biological Diversity (CBD) and the Nagoya Protocol. These treaties require benefit-sharing with the owners of genetic resources. However, whether "genetic resources" include digital sequence information is unsettled. The CBD conceives genetic resources as genetic material containing functional units of heredity. "Material" implies tangibility, and for some scholars, "functional units of heredity," undefined in both treaties, mean full-coding sequences. This article argues that digital sequence information obtained from physical genetic resources, full-coding or not, should be treated as genetic resources. Literal construction of the CBD risks eroding its usefulness and the ABS regime. This is because through bioinformatics, sequence information can easily be obtained from genetic resources for utilization, without physically moving them or concluding ABS agreement with owners. The CBD must evolve with scientific progress also because sequence functionality depends on the state of knowledge. These arguments are vindicated by domestic ABS laws equating genetic information with genetic resources; Nagoya Protocol provisions deeming research exploiting the genetic composition of genetic resources as utilization of genetic resources; and CBD provisions requiring the sharing of benefits from the utilization of genetic resources. Moreover, treaty interpretation and case law demand that generic, scientific terms, such as "genetic resources" and "functional units of heredity" be interpreted in an evolutionary manner to capture scientific developments.

PMID:37008389 | PMC:PMC10043851 | DOI:10.1007/s11569-023-00436-3

Front Cardiovasc Med. 2023 Mar 16;10:1168152. doi: 10.3389/fcvm.2023.1168152. eCollection 2023.

NO ABSTRACT

PMID:37008307 | PMC:PMC10061115 | DOI:10.3389/fcvm.2023.1168152

Front Genet. 2023 Mar 16;14:1128182. doi: 10.3389/fgene.2023.1128182. eCollection 2023.

ABSTRACT

Seed size is not only a yield-related trait but also an important measure to determine the commercial value of groundnut in the international market. For instance, small size is preferred in oil production, whereas large-sized seeds are preferred in confectioneries. In order to identify the genomic regions associated with 100-seed weight (HSW) and shelling percentage (SHP), the recombinant inbred line (RIL) population (Chico × ICGV 02251) of 352 individuals was phenotyped for three seasons and genotyped with an Axiom_Arachis array containing 58K SNPs. A genetic map with 4199 SNP loci was constructed, spanning a map distance of 2708.36 cM. QTL analysis identified six QTLs for SHP, with three consistent QTLs on chromosomes A05, A08, and B10. Similarly, for HSW, seven QTLs located on chromosomes A01, A02, A04, A10, B05, B06, and B09 were identified. BIG SEED locus and spermidine synthase candidate genes associated with seed weight were identified in the QTL region on chromosome B09. Laccase, fibre protein, lipid transfer protein, senescence-associated protein, and disease-resistant NBS-LRR proteins were identified in the QTL regions associated with shelling percentage. The associated markers for major-effect QTLs for both traits successfully distinguished between the small- and large-seeded RILs. QTLs identified for HSW and SHP can be used for developing potential selectable markers to improve the cultivars with desired seed size and shelling percentage to meet the demands of confectionery industries.

PMID:37007937 | PMC:PMC10061104 | DOI:10.3389/fgene.2023.1128182

Front Netw Physiol. 2023 Mar 15;3:1106650. doi: 10.3389/fnetp.2023.1106650. eCollection 2023.

ABSTRACT

Wearable sensors offer new opportunities for the early detection and identification of toxic chemicals in situations where medical evaluation is not immediately possible. We previously found that continuously recorded physiology in guinea pigs can be used for early detection of exposure to an opioid (fentanyl) or a nerve agent (VX), as well as for differentiating between the two. Here, we investigated how exposure to these different chemicals affects the interactions between ECG and respiration parameters as determined by Granger causality (GC). Features reflecting such interactions may provide additional information and improve models differentiating between chemical agents. Traditional respiration and ECG features, as well as GC features, were extracted from data of 120 guinea pigs exposed to VX (n = 61) or fentanyl (n = 59). Data were divided in a training set (n = 99) and a test set (n = 21). Minimum Redundancy Maximum Relevance (mRMR) and Support Vector Machine (SVM) algorithms were used to, respectively, perform feature selection and train a model to discriminate between the two chemicals. We found that ECG and respiration parameters are Granger-related under healthy conditions, and that exposure to fentanyl and VX affected these relationships in different ways. SVM models discriminated between chemicals with accuracy of 95% or higher on the test set. GC features did not improve the classification compared to traditional features. Respiration features (i.e., peak inspiratory and expiratory flow) were the most important to discriminate between different chemical's exposure. Our results indicate that it may be feasible to discriminate between chemical exposure when using traditional physiological respiration features from wearable sensors. Future research will examine whether GC features can contribute to robust detection and differentiation between chemicals when considering other factors, such as generalizing results across species.

PMID:37007435 | PMC:PMC10053028 | DOI:10.3389/fnetp.2023.1106650

Evol Med Public Health. 2022 Dec 19;11(1):80-89. doi: 10.1093/emph/eoac043. eCollection 2023.

ABSTRACT

Non-pharmaceutical interventions (NPIs), such as social distancing and contact tracing, are important public health measures that can reduce pathogen transmission. In addition to playing a crucial role in suppressing transmission, NPIs influence pathogen evolution by mediating mutation supply, restricting the availability of susceptible hosts, and altering the strength of selection for novel variants. Yet it is unclear how NPIs might affect the emergence of novel variants that are able to escape pre-existing immunity (partially or fully), are more transmissible or cause greater mortality. We analyse a stochastic two-strain epidemiological model to determine how the strength and timing of NPIs affect the emergence of variants with similar or contrasting life-history characteristics to the wild type. We show that, while stronger and timelier NPIs generally reduce the likelihood of variant emergence, it is possible for more transmissible variants with high cross-immunity to have a greater probability of emerging at intermediate levels of NPIs. This is because intermediate levels of NPIs allow an epidemic of the wild type that is neither too small (facilitating high mutation supply), nor too large (leaving a large pool of susceptible hosts), to prevent a novel variant from becoming established in the host population. However, since one cannot predict the characteristics of a variant, the best strategy to prevent emergence is likely to be an implementation of strong, timely NPIs.

PMID:37007165 | PMC:PMC10052376 | DOI:10.1093/emph/eoac043

Indian J Hematol Blood Transfus. 2023 Apr;39(2):173-182. doi: 10.1007/s12288-022-01576-4. Epub 2022 Nov 1.

ABSTRACT

HSC transplantation (HSCT) has emerged as a promising treatment option for hematological and immunological disorders. Unfortunately, many viral vectors are inefficient at transduction, limiting the number of cells available for gene therapy in cord blood HSC transplantation. Combining ex vivo expansion and genetic manipulation of cord blood cells is a potential gene therapy approach. We present a 3D co-culture method using a demineralized bone matrix scaffold to optimize lentiviral vector-mediated gene transduction. pLenti-III-miR-GFP-has-miR-124 was transduced into cord blood HSCs. Transduced CD34 + cells co-cultured on the stromal layer for 72 h under cytokine-free conditions. We performed flow cytometry, colony assays, real-time polymerase chain reaction, and SEM morphological analysis. Seventy-two hours after transduction, when pLentiIII-miR-GFP-has-miR-124 and control vector-transduced expanded cord blood HSCs were compared to non-transduced expanded cord blood HSCs, the findings revealed 15 ± 3.04 and 55 ± 3.05-fold increases in miR-124 mRNA expression, respectively. Compared to a control culture on the same day, the expansion of CD34+, CD38-HSCs in 3D culture increased 544 ± 31.09 fold. This result demonstrated that the 3D-culture system could emerge as a novel approach to overcoming the current limitations of cord blood HSC transduction. In the future, this research could be applied in a therapeutic setting.

PMID:37006970 | PMC:PMC10064360 | DOI:10.1007/s12288-022-01576-4

Front Biosci (Landmark Ed). 2023 Mar 6;28(3):46. doi: 10.31083/j.fbl2803046.

ABSTRACT

BACKGROUND: Stefin B, an established model protein for studying the stability and mechanism of protein folding, was used for monitoring protein aggregation and formation of amyloid structure by infrared spectroscopy.

METHODS: The analyses of the integral intensities of the low frequency part of the Amide I band, which is directly connected to the appearance of the cross-β structure reveals the temperature but not pH dependence of stefin B structure.

RESULTS: We show that pH value has significant role in the monomer stability of stefin B. Protein is less stable in acidic environment and becomes more stable in neutral or basic conditions. While in the case of the Amide I band area analysis we apply only spectral regions characteristic for only part of the protein in cross-β structure, the temperature study using multivariate curve resolution (MCR) analysis contains also information about the protein conformation states which do not correspond to native protein nor protein in cross-β structure.

CONCLUSIONS: These facts results in the slightly different shapes of fitted sigmoid functions fitted to the weighted amount of the second basic spectrum (sc2), which is the closed approximation of the protein spectra with cross-β structure. Nevertheless, the applied method detects the initial change of the protein structure. Upon the analysis of infrared data a model for stefin B aggregation is proposed.

PMID:37005760 | DOI:10.31083/j.fbl2803046

Eur Heart J. 2023 Apr 3:ehad170. doi: 10.1093/eurheartj/ehad170. Online ahead of print.

ABSTRACT

There is a pandemic of physical inactivity that appears to parallel the widespread prevalence of cardiovascular disease (CVD). Yet, regular physical activity (PA) and exercise can play an important role not only in primary cardiovascular prevention but also in secondary prevention. This review discusses some of the main cardiovascular effects of PA/exercise and the mechanisms involved, including a healthier metabolic milieu with attenuation of systemic chronic inflammation, as well as adaptations at the vascular (antiatherogenic effects) and heart tissue (myocardial regeneration and cardioprotection) levels. The current evidence for safe implementation of PA and exercise in patients with CVD is also summarized.

PMID:37005351 | DOI:10.1093/eurheartj/ehad170

Biomed Pharmacother. 2023 Mar 31;162:114616. doi: 10.1016/j.biopha.2023.114616. Online ahead of print.

ABSTRACT

With an aging population and the numerous health impacts associated with old age, the identification of anti-aging drugs has become an important new research direction. Although mitochondria have been recognized to affect aging, anti-aging drugs specifically targeting the mitochondria are less well characterized. In this study, diphenyleneiodonium (DPI) was identified as a potential senomorphic drug that functions by promoting mitochondrial fission. DPI significantly reduced the number of senescence-associated β-galactosidase (SA-β-gal) positive cells and increased the number of proliferating Ki-67 positive cells in BrdU or irradiation stress-induced senescent NIH3T3 cells or IMR90 cells and mouse embryonic fibroblasts (MEFs) replicative senescent cells. Cell cycle arrest genes and senescence-associated secretory phenotype (SASP) factors were downregulated with DPI treatment. In addition, the oxygen consumption rate (OCR) of mitochondrial respiration showed that DPI significantly reduced senescence-associated hyper OCR. Mechanistically, DPI promoted mitochondrial fission by enhancing AMPK/MFF phosphorylation and DRP1 mitochondrial translocation. Inhibition of DRP1 by Mdivi-1 abolished DPI-induced mitochondrial fission and the anti-senescence phenotype. Importantly, Eighty-eight-week-old mice treated with DPI had significantly reduced numbers of SA-β-gal positive cells and reduced expression of cell cycle arrest genes and SASP factors in their livers and kidneys. Pathological and functional assays showed DPI treatment not only reduced liver fibrosis and immune cell infiltration but also improved aged-related physical impairments in aged mice. Taken together, our study identified a potential anti-aging compound that exerts its effects through modulation of mitochondrial morphology.

PMID:37004322 | DOI:10.1016/j.biopha.2023.114616

Curr Opin Biotechnol. 2023 Mar 31;81:102922. doi: 10.1016/j.copbio.2023.102922. Online ahead of print.

ABSTRACT

The reproducibility of scientific research is crucial to the success of the scientific method. Here, we review the current best practices when publishing mechanistic models in systems biology. We recommend, where possible, to use software engineering strategies such as testing, verification, validation, documentation, versioning, iterative development, and continuous integration. In addition, adhering to the Findable, Accessible, Interoperable, and Reusable modeling principles allows other scientists to collaborate and build off of each other's work. Existing standards such as Systems Biology Markup Language, CellML, or Simulation Experiment Description Markup Language can greatly improve the likelihood that a published model is reproducible, especially if such models are deposited in well-established model repositories. Where models are published in executable programming languages, the source code and their data should be published as open-source in public code repositories together with any documentation and testing code. For complex models, we recommend container-based solutions where any software dependencies and the run-time context can be easily replicated.

PMID:37004298 | DOI:10.1016/j.copbio.2023.102922

J Exp Bot. 2023 Apr 2:erad123. doi: 10.1093/jxb/erad123. Online ahead of print.

ABSTRACT

Lateral root initiation requires the accumulation of auxin in lateral root founder cells, yielding a local auxin maximum. The positioning of auxin maxima along the primary root determines the density and spacing of lateral roots. The GOLVEN6 (GLV6) and GLV10 signaling peptides and their receptors have been established as regulators of lateral root spacing via their inhibitory effect on lateral root initiation in Arabidopsis. However, it remained unclear how these GLV peptides interfere with auxin signaling or homeostasis. Here, we show that GLV6/10 signaling regulates the expression of a subset of auxin response genes, downstream of the canonical auxin signaling pathway, while simultaneously inhibiting the establishment of auxin maxima within xylem-pole pericycle cells that neighbor lateral root initiation sites. We present genetic evidence that this inhibitory effect relies on the activity of the PIN3 and PIN7 auxin export proteins. Furthermore, GLV6/10 peptide signaling was found to enhance PIN7 abundance in the plasma membranes of xylem-pole pericycle cells, which likely stimulates auxin efflux from these cells. Based on these findings, we propose a model in which the GLV6/10 signaling pathway serves as a negative feedback mechanism that contributes to the robust patterning of auxin maxima along the primary root.

PMID:37004244 | DOI:10.1093/jxb/erad123

Bioinformatics. 2023 Apr 2:btad158. doi: 10.1093/bioinformatics/btad158. Online ahead of print.

ABSTRACT

MOTIVATION: The problem of model inference is of fundamental importance to systems biology. Logical models (e.g., Boolean networks; BNs) represent a computationally attractive approach capable of handling large biological networks. The models are typically inferred from experimental data. However, even with a substantial amount of experimental data supported by some prior knowledge, existing inference methods often focus on a small sample of admissible candidate models only.

RESULTS: We propose Boolean network sketches as a new formal instrument for the inference of Boolean networks. A sketch integrates (typically partial) knowledge about the network's topology and the update logic (obtained through, e.g., a biological knowledge base or a literature search), as well as further assumptions about the properties of the network's transitions (e.g., the form of its attractor landscape), and additional restrictions on the model dynamics given by the measured experimental data. Our new BNs inference algorithm starts with an initial sketch which is extended by adding restrictions representing experimental data to a data-informed sketch and subsequently computes all BNs consistent with the data-informed sketch. Our algorithm is based on a symbolic representation and coloured model-checking. Our approach is unique in its ability to cover a broad spectrum of knowledge and efficiently produce a compact representation of all inferred BNs. We evaluate the method on a non-trivial collection of real-world and simulated data.

AVAILABILITY: All software and data are freely available as a reproducible artefact at https://doi.org/10.5281/zenodo.7688740.

SUPPLEMENTARY INFORMATION: Supplementary data available online through Bioinformatics.

PMID:37004199 | DOI:10.1093/bioinformatics/btad158

Bioinformatics. 2023 Apr 2:btad164. doi: 10.1093/bioinformatics/btad164. Online ahead of print.

ABSTRACT

MOTIVATION: Machine learning has shown extensive growth in recent years and is now routinely applied to sensitive areas. To allow appropriate verification of predictive models before deployment, models must be deterministic. Solely fixing all random seeds is not sufficient for deterministic machine learning, as major machine learning libraries default to the usage of non-deterministic algorithms based on atomic operations.

RESULTS: Various machine learning libraries released deterministic counterparts to the non-deterministic algorithms. We evaluated the effect of these algorithms on determinism and runtime. Based on these results, we formulated a set of requirements for deterministic machine learning and developed a new software solution, the mlf-core ecosystem, which aids machine learning projects to meet and keep these requirements. We applied mlf-core to develop deterministic models in various biomedical fields including a single cell autoencoder with TensorFlow, a PyTorch-based U-Net model for liver-tumor segmentation in CT scans, and a liver cancer classifier based on gene expression profiles with XGBoost.

AVAILABILITY: The complete data together with the implementations of the mlf-core ecosystem and use case models are available at https://github.com/mlf-core.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37004171 | DOI:10.1093/bioinformatics/btad164

Bioinformatics. 2023 Apr 2:btad165. doi: 10.1093/bioinformatics/btad165. Online ahead of print.

ABSTRACT

MOTIVATION: Single-cell RNA-sequencing (scRNA-seq) technologies provide an opportunity to infer cell-specific gene regulatory networks (GRNs) which is an important challenge in systems biology. Although numerous methods have been developed for inferring GRNs from scRNA-seq data, it is still a challenge to deal with cellular heterogeneity.

RESULTS: To address this challenge, we developed an interpretable transformer-based method namely STGRNS for inferring GRNs from scRNA-seq data. In this algorithm, gene expression motif (GEM) technique was proposed to convert gene pairs into contiguous sub-vectors which can be used as input for the transformer encoder. By avoiding missing phase-specific regulations in a network, GEM can improve the accuracy of GRN inference for different types of scRNA-seq data. To assess the performance of STGRNS, we implemented the comparative experiments with some popular methods on extensive benchmark datasets including 21 static and 27 time-series scRNA-seq dataset. All the results show that STGRNS is superior to other comparative methods. In addition, STGRNS was also proved to be more interpretable than "black box" deep learning methods which are well-known for the difficulty to explain the predictions clearly.

AVAILABILITY: The source code and data are available at https://github.com/zhanglab-wbgcas/STGRNS.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37004161 | DOI:10.1093/bioinformatics/btad165

Microb Genom. 2023 Apr;9(4). doi: 10.1099/mgen.0.000990.

ABSTRACT

Sesquiterpene cyclases (STC) catalyse the cyclization of the C15 molecule farnesyl diphosphate into a vast variety of mono- or polycyclic hydrocarbons and, for a few enzymes, oxygenated structures, with diverse stereogenic centres. The huge diversity in sesquiterpene skeleton structures in nature is primarily the result of the type of cyclization driven by the STC. Despite the phenomenal impact of fungal sesquiterpenes on the ecology of fungi and their potentials for applications, the fungal sesquiterpenome is largely untapped. The identification of fungal STC is generally based on protein sequence similarity with characterized enzymes. This approach has improved our knowledge on STC in a few fungal species, but it has limited success for the discovery of distant sequences. Besides, the tools based on secondary metabolite biosynthesis gene clusters have shown poor performance for terpene cyclases. Here, we used four sets of sequences of fungal STC that catalyse four types of cyclization, and specific amino acid motives to identify phylogenetically related sequences in the genomes of basidiomycetes fungi from the order Polyporales. We validated that four STC genes newly identified from the genome sequence of Leiotrametes menziesii, each classified in a different phylogenetic clade, catalysed a predicted cyclization of farnesyl diphosphate. We built HMM models and searched STC genes in 656 fungal genomes genomes. We identified 5605 STC genes, which were classified in one of the four clades and had a predicted cyclization mechanism. We noticed that the HMM models were more accurate for the prediction of the type of cyclization catalysed by basidiomycete STC than for ascomycete STC.

PMID:37073784 | DOI:10.1099/mgen.0.000990

J Mol Cell Cardiol. 2023 Mar 30:S0022-2828(23)00062-7. doi: 10.1016/j.yjmcc.2023.03.015. Online ahead of print.

ABSTRACT

Ca2+ transients (CaT) underlying cardiomyocyte (CM) contraction require efficient Ca2+ coupling between sarcolemmal Ca2+ channels and sarcoplasmic reticulum (SR) ryanodine receptor Ca2+ channels (RyR) for their generation; reduced coupling in disease contributes to diminished CaT and arrhythmogenic Ca2+ events. SR Ca2+ release also occurs via inositol 1,4,5-trisphosphate receptors (InsP3R) in CM. While this pathway contributes negligeably to Ca2+ handling in healthy CM, rodent studies support a role in altered Ca2+ dynamics and arrhythmogenic Ca2+ release involving InsP3R crosstalk with RyRs in disease. Whether this mechanism persists in larger mammals with lower T-tubular density and coupling of RyRs is not fully resolved. We have recently shown an arrhythmogenic action of InsP3-induced Ca2+ release (IICR) in end stage human heart failure, often associated with underlying ischemic heart disease (IHD). How IICR contributes to early stages of disease is however not determined but highly relevant. To access this stage, we chose a porcine model of IHD, which shows substantial remodelling of the area adjacent to the infarct. In cells from this region, IICR preferentially augmented Ca2+ release from non-coupled RyR clusters that otherwise showed delayed activation during the CaT. IICR in turn synchronised Ca2+ release during the CaT but also induced arrhythmogenic delayed afterdepolarizations and action potentials. Nanoscale imaging identified co-clustering of InsP3Rs and RyRs, thereby allowing Ca2+-mediated channel crosstalk. Mathematical modelling supported and further delineated this mechanism of enhanced InsP3R-RyRs coupling in MI. Our findings highlight the role of InsP3R-RyR channel crosstalk in Ca2+ release and arrhythmia during post-MI remodelling.

PMID:37003353 | DOI:10.1016/j.yjmcc.2023.03.015