Bioinformatics. 2023 Oct 20:btad644. doi: 10.1093/bioinformatics/btad644. Online ahead of print.

ABSTRACT

MOTIVATION: The reconstruction of small key regulatory networks that explain the differences in the development of cell (sub)types from single-cell RNA sequencing is a yet unresolved computational problem.

RESULTS: To this end, we have developed SCANet, an all-in-one package for single-cell profiling that covers the whole differential mechanotyping workflow, from inference of trait/cell-type-specific gene co-expression modules, driver gene detection, and transcriptional gene regulatory network reconstruction to mechanistic drug repurposing candidate prediction. To illustrate the power of SCANet, we examined data from two studies. First, we identify the drivers of the mechanotype of a cytokine storm associated with increased mortality in patients with acute respiratory illness. Secondly, we find 20 drugs for 8 potential pharmacological targets in cellular driver mechanisms in the intestinal stem cells of obese mice.

AVAILABILITY: SCANet is a free, open-source, and user-friendly Python package that can be seamlessly integrated into single-cell-based systems medicine research and mechanistic drug discovery.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37862243 | DOI:10.1093/bioinformatics/btad644

OMICS. 2023 Oct;27(10):461-473. doi: 10.1089/omi.2023.0120.

ABSTRACT

Advances in digital health, systems biology, environmental monitoring, and artificial intelligence (AI) continue to revolutionize health care, ushering a precision health future. More than disease treatment and prevention, precision health aims at maintaining good health throughout the lifespan. However, how can precision health impact care for people with a terminal or life-limiting condition? We examine here the ethical, equity, and societal/relational implications of two precision health modalities, (1) integrated systems biology/multi-omics analysis for disease prognostication and (2) digital health technologies for health status monitoring and communication. We focus on three main ethical and societal considerations: benefits and risks associated with integration of these modalities into the palliative care system; inclusion of underrepresented and marginalized groups in technology development and deployment; and the impact of high-tech modalities on palliative care's highly personalized and "high-touch" practice. We conclude with 10 recommendations for ensuring that precision health technologies, such as multi-omics prognostication and digital health monitoring, for palliative care are developed, tested, and implemented ethically, inclusively, and equitably.

PMID:37861713 | DOI:10.1089/omi.2023.0120

OMICS. 2023 Oct;27(10):483-493. doi: 10.1089/omi.2023.0127.

ABSTRACT

Chronic inflammation is an important contributor to tumorigenesis in many tissues. However, the underlying mechanisms of inflammatory signaling in the tumor microenvironment are not yet fully understood in various cancers. Therefore, this study aimed to uncover the gene expression signatures of inflammation-associated proteins that lead to tumorigenesis, and with an eye to discovery of potential system biomarkers and novel drug candidates in oncology. Gene expression profiles associated with 12 common cancers (e.g., breast invasive carcinoma, colon adenocarcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma) from The Cancer Genome Atlas were retrieved and mapped to inflammation-related gene sets. Subsequently, the inflammation-associated differentially expressed genes (i-DEGs) were determined. The i-DEGs common in all cancers were proposed as tumor inflammation signatures (TIS) after pan-cancer analysis. A TIS, consisting of 45 proteins, was evaluated as a potential system biomarker based on its prognostic forecasting and secretion profiles in multiple tissues. In addition, i-DEGs for each cancer type were used as queries for drug repurposing. Narciclasine, parthenolide, and homoharringtonine were identified as potential candidates for drug repurposing. Biomarker candidates in relation to inflammation were identified such as KNG1, SPP1, and MIF. Collectively, these findings inform precision diagnostics development to distinguish individual cancer types, and can also pave the way for novel prognostic decision tools and repurposed drugs across multiple cancers. These new findings and hypotheses warrant further research toward precision/personalized medicine in oncology. Pan-cancer analysis of inflammatory mediators can open up new avenues for innovation in cancer diagnostics and therapeutics.

PMID:37861711 | DOI:10.1089/omi.2023.0127

Elife. 2023 Oct 20;12:e90681. doi: 10.7554/eLife.90681. Online ahead of print.

ABSTRACT

T cells are critically important components of the adaptive immune system primarily responsible for identifying and responding to pathogenic challenges. This recognition of pathogens is driven by the interaction between membrane-bound T cell receptors (TCRs) and antigenic peptides presented on major histocompatibility complex (MHC) molecules. The formation of the TCR-peptide-MHC complex (TCR-pMHC) involves interactions among germline-encoded and hypervariable amino acids. Germline-encoded and hypervariable regions can form contacts critical for complex formation, but only interactions between germline-encoded contacts are likely to be shared across many of all the possible productive TCR-pMHC complexes. Despite this, experimental investigation of these interactions have focused on only a small fraction of the possible interaction space. To address this, we analyzed every possible germline-encoded TCR-MHC contact in humans, thereby generating the first comprehensive characterization of these largely antigen-independent interactions. Our computational analysis suggests that germline-encoded TCR-MHC interactions that are conserved at the sequence level are rare due to the high amino acid diversity of the TCR CDR1 and CDR2 loops, and that such conservation is unlikely to dominate the dynamic protein-protein binding interface. Instead, we propose that binding properties such as the docking orientation are defined by regions of biophysical compatibility between these loops and the MHC surface.

PMID:37861280 | DOI:10.7554/eLife.90681

Plant Biotechnol J. 2023 Oct 20. doi: 10.1111/pbi.14191. Online ahead of print.

NO ABSTRACT

PMID:37861059 | DOI:10.1111/pbi.14191

iScience. 2023 Sep 25;26(10):108042. doi: 10.1016/j.isci.2023.108042. eCollection 2023 Oct 20.

ABSTRACT

Machine learning (ML) has the potential to identify subsets of patients with distinct phenotypes from gene expression data. However, phenotype prediction using ML has often relied on identifying important genes without a systems biology context. To address this, we created an interpretable ML approach based on blood transcriptomics to predict phenotype in systemic lupus erythematosus (SLE), a heterogeneous autoimmune disease. We employed a sequential grouped feature importance algorithm to assess the performance of gene sets, including immune and metabolic pathways and cell types, known to be abnormal in SLE in predicting disease activity and organ involvement. Gene sets related to interferon, tumor necrosis factor, the mitoribosome, and T cell activation were the best predictors of phenotype with excellent performance. These results suggest potential relationships between the molecular pathways identified in each model and manifestations of SLE. This ML approach to phenotype prediction can be applied to other diseases and tissues.

PMID:37860757 | PMC:PMC10582499 | DOI:10.1016/j.isci.2023.108042

iScience. 2023 Sep 28;26(11):108080. doi: 10.1016/j.isci.2023.108080. eCollection 2023 Nov 17.

ABSTRACT

The SARS-CoV-2 genome encodes a multitude of accessory proteins. Using comparative genomic approaches, an additional accessory protein, ORF3c, has been predicted to be encoded within the ORF3a sgmRNA. Expression of ORF3c during infection has been confirmed independently by ribosome profiling. Despite ORF3c also being present in the 2002-2003 SARS-CoV, its function has remained unexplored. Here we show that ORF3c localizes to mitochondria, where it inhibits innate immunity by restricting IFN-β production, but not NF-κB activation or JAK-STAT signaling downstream of type I IFN stimulation. We find that ORF3c is inhibitory after stimulation with cytoplasmic RNA helicases RIG-I or MDA5 or adaptor protein MAVS, but not after TRIF, TBK1 or phospho-IRF3 stimulation. ORF3c co-immunoprecipitates with the antiviral proteins MAVS and PGAM5 and induces MAVS cleavage by caspase-3. Together, these data provide insight into an uncharacterized mechanism of innate immune evasion by this important human pathogen.

PMID:37860693 | PMC:PMC10583119 | DOI:10.1016/j.isci.2023.108080

Front Physiol. 2023 Oct 4;14:1233711. doi: 10.3389/fphys.2023.1233711. eCollection 2023.

ABSTRACT

Despite the important role of bitter taste for the rejection of potentially harmful food sources, birds have long been suspected to exhibit inferior bitter tasting abilities. Although more recent reports on the bitter recognition spectra of several bird species have cast doubt about the validity of this assumption, the bitter taste of avian species is still an understudied field. Previously, we reported the bitter activation profiles of three zebra finch receptors Tas2r5, -r6, and -r7, which represent orthologs of a single chicken bitter taste receptor, Tas2r1. In order to get a better understanding of the bitter tasting capabilities of zebra finches, we selected another Tas2r gene of this species that is similar to another chicken Tas2r. Using functional calcium mobilization experiments, we screened zebra finch Tas2r1 with 72 bitter compounds and observed responses for 7 substances. Interestingly, all but one of the newly identified bitter agonists were different from those previously identified for Tas2r5, -r6, and -r7 suggesting that the newly investigated receptor fills important gaps in the zebra finch bitter recognition profile. The most potent bitter agonist found in our study is cucurbitacin I, a highly toxic natural bitter substance. We conclude that zebra finch exhibits an exquisitely developed bitter taste with pronounced cucurbitacin I sensitivity suggesting a prominent ecological role of this compound for zebra finch.

PMID:37860623 | PMC:PMC10582322 | DOI:10.3389/fphys.2023.1233711

F1000Res. 2023 Apr 13;12:391. doi: 10.12688/f1000research.132952.1. eCollection 2023.

ABSTRACT

Superoxide dismutase [Cu-Zn] 1 (SOD1), is an antioxidant enzyme encoded by the gene SOD1, responsible for regulating oxidative stress levels by sequestering free radicals. Identified as the first gene with mutations in Amyotrophic lateral sclerosis (ALS), SOD1 is a determinant for studying diseases of aging and neurodegeneration. With guidance on well-characterized anti-SOD1 antibodies, the reproducibility of SOD1 research would be enhanced. In this study, we characterized eleven SOD1 commercial antibodies for Western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. We identified many high-performing antibodies and encourage readers to use this report as a guide to select the most appropriate antibody for their specific needs.

PMID:37860271 | PMC:PMC10582621 | DOI:10.12688/f1000research.132952.1

NAR Genom Bioinform. 2023 Oct 18;5(4):lqad092. doi: 10.1093/nargab/lqad092. eCollection 2023 Dec.

ABSTRACT

Given the current status of coronavirus disease 2019 (COVID-19) as a global pandemic, it is of high priority to gain a deeper understanding of the disease's development and how the virus impacts its host. Adenosine (A)-to-Inosine (I) RNA editing is a post-transcriptional modification, catalyzed by the ADAR family of enzymes, that can be considered part of the inherent cellular defense mechanism as it affects the innate immune response in a complex manner. It was previously reported that various viruses could interact with the host's ADAR enzymes, resulting in epigenetic changes both to the virus and the host. Here, we analyze RNA-seq of nasopharyngeal swab specimens as well as whole-blood samples of COVID-19 infected individuals and show a significant elevation in the global RNA editing activity in COVID-19 compared to healthy controls. We also detect specific coding sites that exhibit higher editing activity. We further show that the increment in editing activity during the disease is temporary and returns to baseline shortly after the symptomatic period. These significant epigenetic changes may contribute to the immune system response and affect adverse outcomes seen in post-viral cases.

PMID:37859800 | PMC:PMC10583280 | DOI:10.1093/nargab/lqad092

Exp Neurol. 2023 Oct 17:114578. doi: 10.1016/j.expneurol.2023.114578. Online ahead of print.

ABSTRACT

Traumatic brain injury leads to cellular and circuit changes in the dentate gyrus, a gateway to hippocampal information processing. Intrinsic granule cell firing properties and strong feedback inhibition in the dentate are proposed as critical to its ability to generate unique representation of similar inputs by a process known as pattern separation. Here we evaluate the impact of brain injury on cellular decorrelation of temporally patterned inputs in slices and behavioral discrimination of spatial locations in vivo one week after concussive lateral fluid percussion injury (FPI) in mice. Despite posttraumatic increases in perforant path evoked excitatory drive to granule cells and enhanced ΔFosB labeling, indicating sustained increase in excitability, the reliability of granule cell spiking was not compromised after FPI. Although granule cells continued to effectively decorrelate output spike trains recorded in response to similar temporally patterned input sets after FPI, their ability to decorrelate highly similar input patterns was reduced. In parallel, encoding of similar spatial locations in a novel object location task that involves the dentate inhibitory circuits was impaired one week after FPI. Injury induced changes in pattern separation were accompanied by loss of somatostatin expressing inhibitory neurons in the hilus. Together, these data suggest that the early posttraumatic changes in the dentate circuit undermine dentate circuit decorrelation of temporal input patterns as well as behavioral discrimination of similar spatial locations, both of which could contribute to deficits in episodic memory.

PMID:37858696 | DOI:10.1016/j.expneurol.2023.114578

J Pediatr Surg. 2023 Sep 26:S0022-3468(23)00564-X. doi: 10.1016/j.jpedsurg.2023.09.027. Online ahead of print.

ABSTRACT

PURPOSE: We explored the application of a machine learning algorithm for the timely detection of potential abusive head trauma (AHT) using the first free-text note of an encounter and demographic information.

METHODS: First free-text physician notes and demographic information were collected for children under 5 years of age at a Level 1 Trauma Center. The control group, which included patients with head/neck injury, was compared to those with AHT diagnosed by the Child Protective Team. Differential scores accounted for words overrepresented in AHT patient vs. control notes. Sentiment scores were reflective of note positivity/negativity and subjectivity scores accounted for note subjectivity/objectivity. The composite scores reflected the patient's differential score modified by the subjectivity score. Composite, sentiment, and subjectivity scores combined with demographic information trained a Random Forest (RF) machine learning algorithm to predict AHT.

RESULTS: Final composite scores with demographic information were highly associated with AHT in a test dataset. The control group included 587 patients and the test group included 193 patients. Combining composite scores with demographic information into the RF model improved AHT classification area under the curve (AUC) from 0.68 to 0.78, with an overall accuracy of 84%. Feature importance analysis of our RF model revealed that composite score, sentiment, age, and subjectivity were the most impactful predictors of AHT. The sentiment was not significantly different between control and AHT notes (p = 0.87), while subjectivity trended higher for AHT notes (p = 0.081).

CONCLUSION: We conclude that a machine learning algorithm can recognize patterns within free-text notes and demographic information that aid in AHT detection in children.

LEVEL OF EVIDENCE: III.

PMID:37858394 | DOI:10.1016/j.jpedsurg.2023.09.027

J Colloid Interface Sci. 2023 Oct 6:S0021-9797(23)01928-8. doi: 10.1016/j.jcis.2023.10.015. Online ahead of print.

ABSTRACT

The structure-function characteristics of isolated artificial organelles (AOs) in protocells are mainly known, but there are few reports on clustered or aggregated AOs. To imitate µm-sized complex and heterogeneous cell structures, approaches are needed that enable reversible changes in the aggregation state of colloidal structures in response to chemical, biological, and external stimuli. To construct adaptive organelle-like or cell-like reorganization characteristics, we present an advanced crosslinking strategy to fabricate clustered polymersomes as a platform based on host-guest interactions between azobenzene-containing polymersomes (Azo-Psomes) and a β-cyclodextrin-modified polymer (β-CD polymer) as a crosslinker. First, the reversible (dis)assembly of clustered Azo-Psomes is carried out by the alternating input of crosslinker and adamantane-PEG3000 as a decrosslinker. Moreover, cluster size dependence is demonstrated by environmental pH. These offer the controlled fabrication of various homogeneous and heterogeneous Azo-Psomes structures, including the size regulation and visualization of clustered AOs through a fluorescent enzymatic cascade reaction. Finally, a temperature-sensitive crosslinking agent with β-CD units can promote the coaggregation of Azo-Psomes mediated by temperature changes. Overall, these (co-)clustered Azo-Psomes and their successful transformation in AOs may provide new features for modelling biological systems for eukaryotic cells and systems biology.

PMID:37858368 | DOI:10.1016/j.jcis.2023.10.015

Genome Biol. 2023 Oct 19;24(1):236. doi: 10.1186/s13059-023-03067-9.

ABSTRACT

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets.

PMID:37858253 | DOI:10.1186/s13059-023-03067-9

BMC Biol. 2023 Oct 20;21(1):220. doi: 10.1186/s12915-023-01724-w.

ABSTRACT

BACKGROUND: Through alternative splicing, most human genes produce multiple isoforms in a cell-, tissue-, and disease-specific manner. Numerous studies show that alternative splicing is essential for development, diseases, and their treatments. Despite these important examples, the extent and biological relevance of splicing are currently unknown.

RESULTS: To solve this problem, we developed pairedGSEA and used it to profile transcriptional changes in 100 representative RNA-seq datasets. Our systematic analysis demonstrates that changes in splicing, on average, contribute to 48.1% of the biological signal in expression analyses. Gene-set enrichment analysis furthermore indicates that expression and splicing both convey shared and distinct biological signals.

CONCLUSIONS: These findings establish alternative splicing as a major regulator of the human condition and suggest that most contemporary RNA-seq studies likely miss out on critical biological insights. We anticipate our results will contribute to the transition from a gene-centric to an isoform-centric research paradigm.

PMID:37858135 | DOI:10.1186/s12915-023-01724-w

Nat Genet. 2023 Oct 19. doi: 10.1038/s41588-023-01529-1. Online ahead of print.

ABSTRACT

Most signals in genome-wide association studies (GWAS) of complex traits implicate noncoding genetic variants with putative gene regulatory effects. However, currently identified regulatory variants, notably expression quantitative trait loci (eQTLs), explain only a small fraction of GWAS signals. Here, we show that GWAS and cis-eQTL hits are systematically different: eQTLs cluster strongly near transcription start sites, whereas GWAS hits do not. Genes near GWAS hits are enriched in key functional annotations, are under strong selective constraint and have complex regulatory landscapes across different tissue/cell types, whereas genes near eQTLs are depleted of most functional annotations, show relaxed constraint, and have simpler regulatory landscapes. We describe a model to understand these observations, including how natural selection on complex traits hinders discovery of functionally relevant eQTLs. Our results imply that GWAS and eQTL studies are systematically biased toward different types of variant, and support the use of complementary functional approaches alongside the next generation of eQTL studies.

PMID:37857933 | DOI:10.1038/s41588-023-01529-1

Nat Metab. 2023 Oct 19. doi: 10.1038/s42255-023-00908-6. Online ahead of print.

ABSTRACT

Metabolic regulation is integral to the proper functioning of innate lymphoid cells, yet the underlying mechanisms remain elusive. Here, we show that disruption of exogenous proline uptake, either through dietary restriction or by deficiency of the proline transporter Slc6a7, in lymphoid tissue inducer (LTi) cells, impairs LTi activation and aggravates dextran sodium sulfate-induced colitis in mice. With an integrative transcriptomic and metabolomic analysis, we profile the metabolic characteristics of various innate lymphoid cell subsets and reveal a notable enrichment of proline metabolism in LTi cells. Mechanistically, defective proline uptake diminishes the generation of reactive oxygen species, previously known to facilitate LTi activation. Additionally, LTi cells deficient in Slc6a7 display downregulation of Cebpb and Kdm6b, resulting in compromised transcriptional and epigenetic regulation of interleukin-22. Furthermore, our study uncovers the therapeutic potential of proline supplementation in alleviating colitis. Therefore, these findings shed light on the role of proline in facilitating LTi activation and ultimately contributing to gut homeostasis.

PMID:37857730 | DOI:10.1038/s42255-023-00908-6

Sci Rep. 2023 Oct 19;13(1):17874. doi: 10.1038/s41598-023-44426-7.

ABSTRACT

Efficacious stem cell-based therapies for traumatic brain injury (TBI) depend on successful delivery, migration, and engraftment of stem cells to induce neuroprotection. L-myc expressing human neural stem cells (LMNSC008) demonstrate an inherent tropism to injury sites after intranasal (IN) administration. We hypothesize that IN delivered LMNSC008 cells migrate to primary and secondary injury sites and modulate biomarkers associated with neuroprotection and tissue regeneration. To test this hypothesis, immunocompetent adult female rats received either controlled cortical impact injury or sham surgery. LMNSC008 cells or a vehicle were administered IN on postoperative days 7, 9, 11, 13, 15, and 17. The distribution and migration of eGFP-expressing LMNSC008 cells were quantified over 1 mm-thick optically cleared (CLARITY) coronal brain sections from TBI and SHAM controls. NSC migration was observed along white matter tracts projecting toward the hippocampus and regions of TBI. ELISA and Nanostring assays revealed a shift in tissue gene expression in LMNSC008 treated rats relative to controls. LMNSC008 treatment reduced expression of genes and pathways involved in inflammatory response, microglial function, and various cytokines and receptors. Our proof-of-concept studies, although preliminary, support the rationale of using intranasal delivery of LMNSC008 cells for functional studies in preclinical models of TBI and provide support for potential translatability in TBI patients.

PMID:37857701 | DOI:10.1038/s41598-023-44426-7

Sci Rep. 2023 Oct 19;13(1):17881. doi: 10.1038/s41598-023-45018-1.

ABSTRACT

We present a miniature oblique back-illumination microscope (mOBM) for imaging the microcirculation of human oral mucosa, enabling real-time, label-free phase contrast imaging of individual leukocytes circulating in the bloodstream, as well as their rolling and adhesion on vascular walls-the initial steps in leukocyte recruitment that is a hallmark of inflammation. Using the mOBM system, we studied the leukocyte-endothelial interactions in healthy and locally inflamed tissue and observed drastic changes in leukocyte movement (velocity and displacement profile). Our findings suggest that real-time imaging of leukocyte dynamics can provide new diagnostic insights (assessment of inflammation, temporal progression of disease, evaluation of therapeutic response, etc.) that are not available using conventional static parameters such as cell number and morphology.

PMID:37857684 | DOI:10.1038/s41598-023-45018-1

NPJ Syst Biol Appl. 2023 Oct 19;9(1):51. doi: 10.1038/s41540-023-00312-6.

ABSTRACT

Inferring gene regulatory networks (GRNs) is a fundamental challenge in biology that aims to unravel the complex relationships between genes and their regulators. Deciphering these networks plays a critical role in understanding the underlying regulatory crosstalk that drives many cellular processes and diseases. Recent advances in sequencing technology have led to the development of state-of-the-art GRN inference methods that exploit matched single-cell multi-omic data. By employing diverse mathematical and statistical methodologies, these methods aim to reconstruct more comprehensive and precise gene regulatory networks. In this review, we give a brief overview on the statistical and methodological foundations commonly used in GRN inference methods. We then compare and contrast the latest state-of-the-art GRN inference methods for single-cell matched multi-omics data, and discuss their assumptions, limitations and opportunities. Finally, we discuss the challenges and future directions that hold promise for further advancements in this rapidly developing field.

PMID:37857632 | DOI:10.1038/s41540-023-00312-6