Biomaterials. 2024 Mar 9;307:122525. doi: 10.1016/j.biomaterials.2024.122525. Online ahead of print.

ABSTRACT

Candida albicans is a commensal yeast of the human intestinal microbiota that, under predisposing conditions, can become pathogenic and cause life-threatening systemic infections (candidiasis). Fungal-host interactions during candidiasis are commonly studied using conventional 2D in vitro models, which have provided critical insights into the pathogenicity. However, microphysiological models with a higher biological complexity may be more suitable to mimic in vivo-like infection processes and antifungal drug efficacy. Therefore, a 3D intestine-on-chip model was used to investigate fungal-host interactions during the onset of invasive candidiasis and evaluate antifungal treatment under clinically relevant conditions. By combining microbiological and image-based analyses we quantified infection processes such as invasiveness and fungal translocation across the epithelial barrier. Additionally, we obtained novel insights into fungal microcolony morphology and association with the tissue. Our results demonstrate that C. albicans microcolonies induce injury to the epithelial tissue by disrupting apical cell-cell contacts and causing inflammation. Caspofungin treatment effectively reduced the fungal biomass and induced substantial alterations in microcolony morphology during infection with a wild-type strain. However, caspofungin showed limited effects after infection with an echinocandin-resistant clinical isolate. Collectively, this organ-on-chip model can be leveraged for in-depth characterization of pathogen-host interactions and alterations due to antimicrobial treatment.

PMID:38489910 | DOI:10.1016/j.biomaterials.2024.122525

Cell Rep. 2024 Mar 13;43(3):113956. doi: 10.1016/j.celrep.2024.113956. Online ahead of print.

ABSTRACT

Drugs of abuse can persistently change the reward circuit in ways that contribute to relapse behavior, partly via mechanisms that regulate chromatin structure and function. Nuclear orphan receptor subfamily4 groupA member2 (NR4A2, also known as NURR1) is an important effector of histone deacetylase 3 (HDAC3)-dependent mechanisms in persistent memory processes and is highly expressed in the medial habenula (MHb), a region that regulates nicotine-associated behaviors. Here, expressing the Nr4a2 dominant negative (Nurr2c) in the MHb blocks reinstatement of cocaine seeking in mice. We use single-nucleus transcriptomics to characterize the molecular cascade following Nr4a2 manipulation, revealing changes in transcriptional networks related to addiction, neuroplasticity, and GABAergic and glutamatergic signaling. The network controlled by NR4A2 is characterized using a transcription factor regulatory network inference algorithm. These results identify the MHb as a pivotal regulator of relapse behavior and demonstrate the importance of NR4A2 as a key mechanism driving the MHb component of relapse.

PMID:38489267 | DOI:10.1016/j.celrep.2024.113956

J Alzheimers Dis. 2024 Mar 12. doi: 10.3233/JAD-231184. Online ahead of print.

ABSTRACT

A hypothesis of Alzheimer's disease etiology is proposed describing how cellular stress induces excessive polyamine synthesis and recycling which can disrupt nucleoli. Polyamines are essential in nucleolar functions, such as RNA folding and ribonucleoprotein assembly. Changes in the nucleolar pool of anionic RNA and cationic polyamines acting as counterions can cause significant nucleolar dynamics. Polyamine synthesis reduces S-adenosylmethionine which, at low levels, triggers tau phosphorylation. Also, polyamine recycling reduces acetyl-CoA needed for acetylcholine, which is low in Alzheimer's disease. Extraordinary nucleolar expansion and/or contraction can disrupt epigenetic control in peri-nucleolar chromatin, such as chromosome 14 with the presenilin-1 gene; chromosome 21 with the amyloid precursor protein gene; chromosome 17 with the tau gene; chromosome 19 with the APOE4 gene; and the inactive X chromosome (Xi; aka "nucleolar satellite") with normally silent spermine synthase (polyamine synthesis) and spermidine/spermine-N1-acetyltransferase (polyamine recycling) alleles. Chromosomes 17, 19 and the Xi have high concentrations of Alu elements which can be transcribed by RNA polymerase III if positioned nucleosomes are displaced from the Alu elements. A sudden flood of Alu RNA transcripts can competitively bind nucleolin which is usually bound to Alu sequences in structural RNAs that stabilize the nucleolar heterochromatic shell. This Alu competition leads to loss of nucleolar integrity with leaking of nucleolar polyamines that cause aggregation of phosphorylated tau. The hypothesis was developed with key word searches (e.g., PubMed) using relevant terms (e.g., Alzheimer's, lupus, nucleolin) based on a systems biology approach and exploring autoimmune disease tautology, gaining synergistic insights from other diseases.

PMID:38489184 | DOI:10.3233/JAD-231184

Gigascience. 2024 Jan 2;13:giae005. doi: 10.1093/gigascience/giae005.

ABSTRACT

In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.

PMID:38488666 | DOI:10.1093/gigascience/giae005

Cancer Res. 2024 Mar 15. doi: 10.1158/0008-5472.CAN-23-2657. Online ahead of print.

ABSTRACT

The NCI's Cloud Resources (CRs) are the analytical components of the Cancer Research Data Commons (CRDC) ecosystem. This review describes how the three CRs (Broad Institute FireCloud, Institute for Systems Biology Cancer Gateway in the Cloud, and Seven Bridges Cancer Genomics Cloud) provide access and availability to large, cloud-hosted, multi-modal cancer datasets, as well as offer tools and workspaces for performing data analysis where the data resides, without download or storage. In addition, users can upload their own data and tools into their workspaces, allowing researchers to create custom analysis workflows and integrate CRDC-hosted data with their own.

PMID:38488504 | DOI:10.1158/0008-5472.CAN-23-2657

New Phytol. 2024 Mar 15. doi: 10.1111/nph.19660. Online ahead of print.

ABSTRACT

Community genetics seeks to understand the mechanisms by which natural genetic variation in heritable host phenotypes can encompass assemblages of organisms such as bacteria, fungi, and many animals including arthropods. Prior studies that focused on plant genotypes have been unable to identify genes controlling community composition, a necessary step to predict ecosystem structure and function as underlying genes shift within plant populations. We surveyed arthropods within an association population of Populus trichocarpa in three common gardens to discover plant genes that contributed to arthropod community composition. We analyzed our surveys with traditional single-trait genome-wide association analysis (GWAS), multitrait GWAS, and functional networks built from a diverse set of plant phenotypes. Plant genotype was influential in structuring arthropod community composition among several garden sites. Candidate genes important for higher level organization of arthropod communities had broadly applicable functions, such as terpenoid biosynthesis and production of dsRNA binding proteins and protein kinases, which may be capable of targeting multiple arthropod species. We have demonstrated the ability to detect, in an uncontrolled environment, individual genes that are associated with the community assemblage of arthropods on a host plant, further enhancing our understanding of genetic mechanisms that impact ecosystem structure.

PMID:38488269 | DOI:10.1111/nph.19660

Elife. 2024 Mar 15;12:RP91415. doi: 10.7554/eLife.91415.

ABSTRACT

Accurately detecting distant evolutionary relationships between proteins remains an ongoing challenge in bioinformatics. Search methods based on primary sequence struggle to accurately detect homology between sequences with less than 20% amino acid identity. Profile- and structure-based strategies extend sensitive search capabilities into this twilight zone of sequence similarity but require slow pre-processing steps. Recently, whole-protein and positional embeddings from deep neural networks have shown promise for providing sensitive sequence comparison and annotation at long evolutionary distances. Embeddings are generally faster to compute than profiles and predicted structures but still suffer several drawbacks related to the ability of whole-protein embeddings to discriminate domain-level homology, and the database size and search speed of methods using positional embeddings. In this work, we show that low-dimensionality positional embeddings can be used directly in speed-optimized local search algorithms. As a proof of concept, we use the ESM2 3B model to convert primary sequences directly into the 3D interaction (3Di) alphabet or amino acid profiles and use these embeddings as input to the highly optimized Foldseek, HMMER3, and HH-suite search algorithms. Our results suggest that positional embeddings as small as a single byte can provide sufficient information for dramatically improved sensitivity over amino acid sequence searches without sacrificing search speed.

PMID:38488154 | DOI:10.7554/eLife.91415

Patterns (N Y). 2024 Feb 21;5(3):100933. doi: 10.1016/j.patter.2024.100933. eCollection 2024 Mar 8.

ABSTRACT

In cancer research, pathology report text is a largely untapped data source. Pathology reports are routinely generated, more nuanced than structured data, and contain added insight from pathologists. However, there are no publicly available datasets for benchmarking report-based models. Two recent advances suggest the urgent need for a benchmark dataset. First, improved optical character recognition (OCR) techniques will make it possible to access older pathology reports in an automated way, increasing the data available for analysis. Second, recent improvements in natural language processing (NLP) techniques using artificial intelligence (AI) allow more accurate prediction of clinical targets from text. We apply state-of-the-art OCR and customized post-processing to report PDFs from The Cancer Genome Atlas, generating a machine-readable corpus of 9,523 reports. Finally, we perform a proof-of-principle cancer-type classification across 32 tissues, achieving 0.992 average AU-ROC. This dataset will be useful to researchers across specialties, including research clinicians, clinical trial investigators, and clinical NLP researchers.

PMID:38487800 | PMC:PMC10935496 | DOI:10.1016/j.patter.2024.100933

Hortic Res. 2024 Jan 2;11(2):uhad294. doi: 10.1093/hr/uhad294. eCollection 2024 Feb.

ABSTRACT

Peach is a model for Prunus genetics and genomics, however, identifying and validating genes associated to peach breeding traits is a complex task. A gene coexpression network (GCN) capable of capturing stable gene-gene relationships would help researchers overcome the intrinsic limitations of peach genetics and genomics approaches and outline future research opportunities. In this study, we created four GCNs from 604 Illumina RNA-Seq libraries. We evaluated the performance of every GCN in predicting functional annotations using an algorithm based on the 'guilty-by-association' principle. The GCN with the best performance was COO300, encompassing 21 956 genes. To validate its performance predicting gene function, we performed two case studies. In case study 1, we used two genes involved in fruit flesh softening: the endopolygalacturonases PpPG21 and PpPG22. Genes coexpressing with both genes were extracted and referred to as melting flesh (MF) network. Finally, we performed an enrichment analysis of MF network and compared the results with the current knowledge regarding peach fruit softening. The MF network mostly included genes involved in cell wall expansion and remodeling, and with expressions triggered by ripening-related phytohormones, such as ethylene, auxin, and methyl jasmonate. In case study 2, we explored potential targets of the anthocyanin regulator PpMYB10.1 by comparing its gene-centered coexpression network with that of its grapevine orthologues, identifying a common regulatory network. These results validated COO300 as a powerful tool for peach and Prunus research. This network, renamed as PeachGCN v1.0, and the scripts required to perform a function prediction analysis are available at https://github.com/felipecobos/PeachGCN.

PMID:38487296 | PMC:PMC10939413 | DOI:10.1093/hr/uhad294

iScience. 2024 Feb 24;27(3):109327. doi: 10.1016/j.isci.2024.109327. eCollection 2024 Mar 15.

ABSTRACT

Emerging studies have demonstrated the link between RNA modifications and various cancers, while the predictive value and functional mechanisms of RNA modification-related genes (RMGs) in esophageal squamous cell carcinoma (ESCC) remain unclear. Here we established a prognostic signature for ESCC based on five RMGs. The analysis of ESCC clinical samples further verified the prognostic power of the prognostic signature. Moreover, we found that the knockdown of NSUN6 promotes ESCC progression in vitro and in vivo, whereas the overexpression of NSUN6 inhibits the malignant phenotype of ESCC cells. Mechanically, NSUN6 mediated tRNA m5C modifications selectively enhance the translation efficiency of CDH1 mRNA in a codon dependent manner. Rescue assays revealed that E-cadherin is an essential downstream target that mediates NSUN6's function in the regulation of ESCC progression. These findings offer additional insights into the link between ESCC and RMGs, as well as provide potential strategies for ESCC management and therapy.

PMID:38487015 | PMC:PMC10937836 | DOI:10.1016/j.isci.2024.109327

NAR Genom Bioinform. 2024 Feb 15;6(1):lqae014. doi: 10.1093/nargab/lqae014. eCollection 2024 Mar.

ABSTRACT

Protein homeostasis (a.k.a. proteostasis) is associated with the primary functions of life, and therefore with evolution. However, it is unclear how cellular proteostasis machines have evolved to adjust protein biogenesis needs to environmental constraints. Herein, we describe a novel computational approach, based on semantic network analysis, to evaluate proteostasis plasticity during evolution. We show that the molecular components of the proteostasis network (PN) are reliable metrics to deconvolute the life forms into Archaea, Bacteria and Eukarya and to assess the evolution rates among species. Semantic graphs were used as new criteria to evaluate PN complexity in 93 Eukarya, 250 Bacteria and 62 Archaea, thus representing a novel strategy for taxonomic classification, which provided information about species divergence. Kingdom-specific PN components were identified, suggesting that PN complexity may correlate with evolution. We found that the gains that occurred throughout PN evolution revealed a dichotomy within both the PN conserved modules and within kingdom-specific modules. Additionally, many of these components contribute to the evolutionary imprinting of other conserved mechanisms. Finally, the current study suggests a new way to exploit the genomic annotation of biomedical ontologies, deriving new knowledge from the semantic comparison of different biological systems.

PMID:38486886 | PMC:PMC10939379 | DOI:10.1093/nargab/lqae014

Cell Host Microbe. 2024 Mar 13;32(3):298-300. doi: 10.1016/j.chom.2024.02.008.

ABSTRACT

Pyridoxine-unresponsive homocystinuria has lifelong implications for health. In this issue, Perreault and colleagues present evidence that orally delivered engineered probiotic Escherichia Coli Nissle SYNB1353 is a promising candidate in reducing homocysteine, with successful trials in mice, monkeys, and humans. However, further probiotic optimization and safety assessments are required.

PMID:38484708 | DOI:10.1016/j.chom.2024.02.008

Cell Host Microbe. 2024 Mar 13;32(3):293-295. doi: 10.1016/j.chom.2024.02.009.

ABSTRACT

In this issue of Cell Host & Microbe, Carasso et al. survey invertible DNA sites in Bacteroidales from patients with inflammatory bowel disease (IBD) and healthy control individuals. They identify complex functional interactions between Bacteroides fragilis, an invertible promoter, a capsular polysaccharide, a bacteriophage, and the human host. The establishment of 'omics approaches to characterizing genomic targets and functional roles is still required.

PMID:38484706 | DOI:10.1016/j.chom.2024.02.009

OMICS. 2024 Mar 14. doi: 10.1089/omi.2023.0285. Online ahead of print.

ABSTRACT

Breast cancer is the lead cause of cancer-related deaths among women globally. Breast cancer metastasis is a complex and still inadequately understood process and a key dimension of mortality attendant to breast cancer. This study reports dysregulated genes across metastatic stages and tissues, shedding light on their molecular interplay in disease pathogenesis and new possibilities for drug discovery. Comprehensive analyses of gene expression data from primary breast tumor, circulating tumor cells, and distant metastatic sites in the brain, lung, liver, and bone were conducted. Genes dysregulated across multiple stages and tissues were identified as metastatic cascade genes, and are further classified based on functional associations with metastasis-related mechanisms. Their interactions with HUB genes in interactome networks were scrutinized, followed by pathway enrichment analysis. Validation for their potential as targets included assessments for survival, druggability, prognostic marker status, secretome annotation, protein expression, and cell type marker association. Results displayed critical genes in the metastatic cascade and those specific to metastatic sites, revealing the involvement of the collagen degradation and assembly of collagen fibrils and other multimeric structure pathways in driving metastasis. Notably, pivotal cascade genes FABP4, CXCL12, APOD, and IGF1 emerged with high metastatic potential, linked to significant druggability and survival scores, establishing them as potential molecular targets. The significance of this research lies in its potential to uncover novel biomarkers for early detection, therapeutic targets, and a deeper understanding of the molecular mechanisms underpinning the metastatic cascade in breast cancer, and with an eye to precision/personalized medicine.

PMID:38484298 | DOI:10.1089/omi.2023.0285

Science. 2024 Mar 14:eadk7368. doi: 10.1126/science.adk7368. Online ahead of print.

ABSTRACT

Numerous nonantibiotic drugs have potent antibacterial activity and can adversely impact the human microbiome. The mechanistic underpinning of this toxicity remains largely unknown. We investigated the antibacterial activity of 200 drugs using genetic screens with thousands of barcoded Escherichia coli knockouts. We analyzed 2 million gene-drug interactions underlying drug-specific toxicity. Network-based analysis of drug-drug similarities revealed that antibiotics clustered into modules consistent with the mode of action of their established classes, while nonantibiotics remained unconnected. Half of the nonantibiotics clustered into separate modules, potentially revealing shared and unexploited targets for novel antimicrobials. Analysis of efflux systems revealed they widely impact antibiotics and nonantibiotics alike, suggesting that the impact of nonantibiotics on antibiotic cross-resistance should be investigated closely in vivo.

PMID:38484036 | DOI:10.1126/science.adk7368

PLoS Comput Biol. 2024 Mar 14;20(3):e1011440. doi: 10.1371/journal.pcbi.1011440. Online ahead of print.

ABSTRACT

Vector control is a vital tool utilised by malaria control and elimination programmes worldwide, and as such it is important that we can accurately quantify the expected public health impact of these methods. There are very few previous models that consider vector-control-induced changes in the age-structure of the vector population and the resulting impact on transmission. We analytically derive the steady-state solution of a novel age-structured deterministic compartmental model describing the mosquito feeding cycle, with mosquito age represented discretely by parity-the number of cycles (or successful bloodmeals) completed. Our key model output comprises an explicit, analytically tractable solution that can be used to directly quantify key transmission statistics, such as the effective reproductive ratio under control, Rc, and investigate the age-structured impact of vector control. Application of this model reinforces current knowledge that adult-acting interventions, such as indoor residual spraying of insecticides (IRS) or long-lasting insecticidal nets (LLINs), can be highly effective at reducing transmission, due to the dual effects of repelling and killing mosquitoes. We also demonstrate how larval measures can be implemented in addition to adult-acting measures to reduce Rc and mitigate the impact of waning insecticidal efficacy, as well as how mid-ranges of LLIN coverage are likely to experience the largest effect of reduced net integrity on transmission. We conclude that whilst well-maintained adult-acting vector control measures are substantially more effective than larval-based interventions, incorporating larval control in existing LLIN or IRS programmes could substantially reduce transmission and help mitigate any waning effects of adult-acting measures.

PMID:38484022 | DOI:10.1371/journal.pcbi.1011440

Proc Natl Acad Sci U S A. 2024 Mar 19;121(12):e2318176121. doi: 10.1073/pnas.2318176121. Epub 2024 Mar 14.

ABSTRACT

Endogenous retroviruses (ERVs) are frequently reactivated in mammalian placenta. It has been proposed that ERVs contribute to shaping the gene regulatory network of mammalian trophoblasts, dominantly acting as species- and placental-specific enhancers. However, whether and how ERVs control human trophoblast development through alternative pathways remains poorly understood. Besides the well-recognized function of human endogenous retrovirus-H (HERVH) in maintaining pluripotency of early human epiblast, here we present a unique role of HERVH on trophoblast lineage development. We found that the LTR7C/HERVH subfamily exhibits an accessible chromatin state in the human trophoblast lineage. Particularly, the LTR7C/HERVH-derived Urothelial Cancer Associated 1 (UCA1), a primate-specific long non-coding RNA (lncRNA), is transcribed in human trophoblasts and promotes the proliferation of human trophoblast stem cells (hTSCs), whereas its ectopic expression compromises human trophoblast syncytialization coinciding with increased interferon signaling pathway. Importantly, UCA1 upregulation is detectable in placental samples from early-onset preeclampsia (EO-PE) patients and the transcriptome of EO-PE placenta exhibits considerable similarities to that of the syncytiotrophoblasts differentiated from UCA1-overexpressing hTSCs, supporting up-regulated UCA1 as a potential biomarker of this disease. Altogether, our data shed light on the versatile regulatory role of HERVH in early human development and provide a unique mechanism whereby ERVs exert a function in human placentation and placental syndromes.

PMID:38483994 | DOI:10.1073/pnas.2318176121

Elife. 2024 Mar 14;13:e82564. doi: 10.7554/eLife.82564.

ABSTRACT

Genome-wide association studies (GWAS) identified thousands of genetic variants linked to phenotypic traits and disease risk. However, mechanistic understanding of how GWAS variants influence complex morphological traits and can, in certain cases, simultaneously confer normal-range phenotypic variation and disease predisposition, is still largely lacking. Here, we focus on rs6740960, a single nucleotide polymorphism (SNP) at the 2p21 locus, which in GWAS studies has been associated both with normal-range variation in jaw shape and with an increased risk of non-syndromic orofacial clefting. Using in vitro derived embryonic cell types relevant for human facial morphogenesis, we show that this SNP resides in an enhancer that regulates chondrocytic expression of PKDCC - a gene encoding a tyrosine kinase involved in chondrogenesis and skeletal development. In agreement, we demonstrate that the rs6740960 SNP is sufficient to confer chondrocyte-specific differences in PKDCC expression. By deploying dense landmark morphometric analysis of skull elements in mice, we show that changes in Pkdcc dosage are associated with quantitative changes in the maxilla, mandible, and palatine bone shape that are concordant with the facial phenotypes and disease predisposition seen in humans. We further demonstrate that the frequency of the rs6740960 variant strongly deviated among different human populations, and that the activity of its cognate enhancer diverged in hominids. Our study provides a mechanistic explanation of how a common SNP can mediate normal-range and disease-associated morphological variation, with implications for the evolution of human facial features.

PMID:38483448 | DOI:10.7554/eLife.82564

Health Secur. 2024 Mar 13. doi: 10.1089/hs.2023.0076. Online ahead of print.

NO ABSTRACT

PMID:38483337 | DOI:10.1089/hs.2023.0076

Physiol Rev. 2024 Mar 14. doi: 10.1152/physrev.00042.2023. Online ahead of print.

ABSTRACT

Stress resilience is the phenomenon that some people maintain their mental health despite exposure to adversity or show only temporary impairments followed by quick recovery. Resilience research attempts to unravel the factors and mechanisms that make resilience possible and to harness its insights for the development of preventative interventions in individuals at risk for acquiring stress-related dysfunctions. Biological resilience research has been lagging behind the psychological and social sciences, but has seen a massive surge in recent years. At the same time, progress in this field has been hampered by methodological challenges related to finding suitable operationalizations and study designs, replicating findings, and modeling resilience in animals. We embed a review of behavioral, neuroimaging, neurobiological, and systems-biological findings in adults in a critical methods discussion. We find preliminary evidence that hippocampal-based pattern separation and prefrontal-based cognitive control functions protect against the development of pathological fears in the aftermath of singular, event-type stressors (as found in fear-related disorders, including simpler forms of post-traumatic stress disorder, PTSD), by facilitating the perception of safety. Reward system-based pursuit and savoring of positive reinforcers appear to protect against the development of more generalized dysfunctions of the anxious-depressive spectrum resulting from more severe or longer-lasting stressors (as in depression, generalized or comorbid anxiety, or severe PTSD). Links between preserved functioning of these neural systems under stress and neuroplasticity, immunoregulation, gut microbiome composition, and integrity of the gut barrier and the blood-brain barrier are beginning to emerge. On this basis, avenues for biological interventions are pointed out.

PMID:38483288 | DOI:10.1152/physrev.00042.2023