Methods Mol Biol. 2023;2718:99-110. doi: 10.1007/978-1-0716-3457-8_6.

ABSTRACT

Many proteolytic cleavage events cannot be covered with conventional trypsin-based N-terminomics workflows. These typically involve the derivatization of protein N-termini and Lys residues as an initial step, such that trypsin will cleave C-terminal of arginine but not lysine residues (ArgC-like cleavage). From 20,422 reviewed human protein sequences in Uniprot, 3597 have known N-terminal signal peptides. An in silico ArgC-like digestion of the corresponding 3597 mature protein sequences reveals that-even for these well-known and well-studied proteolytic events-trypsin-based N-terminomics workflows may miss up to 50% of signaling cleavage events as the corresponding neo-N-terminal peptides will have an unfavorable length of <7 (875 peptides) or >30 (911 peptides) amino acids. In this chapter, we provide a protocol that can be applied to all kinds of samples to improve access to this "inaccessible" N-terminome, by making use of the alternative, broad-specificity protease subtilisin for fast and reproducible digestion of proteins.

PMID:37665456 | DOI:10.1007/978-1-0716-3457-8_6

Nucleic Acids Res. 2023 Sep 4:gkad712. doi: 10.1093/nar/gkad712. Online ahead of print.

ABSTRACT

The Open Genes database was created to enhance and simplify the search for potential aging therapy targets. We collected data on 2402 genes associated with aging and developed convenient tools for searching and comparing gene features. A comprehensive description of genes has been provided, including lifespan-extending interventions, age-related changes, longevity associations, gene evolution, associations with diseases and hallmarks of aging, and functions of gene products. For each experiment, we presented the necessary structured data for evaluating the experiment's quality and interpreting the study's findings. Our goal was to stay objective and precise while connecting a particular gene to human aging. We distinguished six types of studies and 12 criteria for adding genes to our database. Genes were classified according to the confidence level of the link between the gene and aging. All the data collected in a database are provided both by an API and a user interface. The database is publicly available on a website at https://open-genes.org/.

PMID:37665017 | DOI:10.1093/nar/gkad712

Front Biosci (Landmark Ed). 2023 Aug 25;28(8):179. doi: 10.31083/j.fbl2808179.

ABSTRACT

BACKGROUND: Cerebral ischemia-reperfusion injury (CIR) following a stroke results in secondary damage and is a leading cause of adult disability. The present study aimed to identify hub genes and networks in CIR to explore potential therapeutic agents for its treatment.

METHODS: Differentially expressed genes based on the GSE23163 dataset were identified, and weighted gene co-expression network analysis was performed to explore co-expression modules associated with CIR. Hub genes were identified by intersecting immune gene profiles, differentially expressed genes, and modular genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and transcription factor-microRNA-gene regulatory network analyses were then conducted in selected crucial modules. Subsequently, their expression levels in animal models were verified using real-time quantitative polymerase chain reaction and Western blotting. Finally, potential drug molecules were screened for, and molecular docking simulations were performed to identify potential therapeutic targets.

RESULTS: Seven hub genes-namely, Ccl3, Ccl4, Ccl7, Cxcl1, Hspa1a, Cd14, and Socs3-were identified. Furthermore, we established a protein interaction network using the STRING database and found that the core genes selected through the cytohubba plugin remained consistent. Animal experiments showed that at the transcriptional level, all seven genes showed significant differences (p < 0.001, fold change vs sham, 5-200). At the translational level, however, only Ccl3, Ccl4, Ccl7, Hspa1a, and Socs3 showed significant differences, while Cxcl1 and Cd14 did not. Nifedipine, with the highest predicted score, was identified as a therapeutic agent and successfully docked with the protein encoded by the hub genes.

CONCLUSIONS: The expression of Ccl3, Ccl4, Ccl7, Hspa1a, and Socs3 was significantly different in CIR tissues compared to normal tissues both at the transcriptional and translational levels. Systems biology approaches indicated that these could be possible CIR marker genes, providing a stepping stone for further experimental studies.

PMID:37664920 | DOI:10.31083/j.fbl2808179

iScience. 2023 Aug 9;26(9):107576. doi: 10.1016/j.isci.2023.107576. eCollection 2023 Sep 15.

ABSTRACT

Heritability in the immune tumor microenvironment (iTME) has been widely observed yet remains largely uncharacterized. Here, we developed a machine learning approach to map iTME modifiers within loci from genome-wide association studies (GWASs) for breast cancer (BrCa) incidence. A random forest model was trained on a positive set of immune-oncology (I-O) targets, and then used to assign I-O target probability scores to 1,362 candidate genes in linkage disequilibrium with 155 BrCa GWAS loci. Cluster analysis of the most probable candidates revealed two subfamilies of genes related to effector functions and adaptive immune responses, suggesting that iTME modifiers impact multiple aspects of anticancer immunity. Two of the top ranking BrCa candidates, LSP1 and TLR1, were orthogonally validated as iTME modifiers using BrCa patient biopsies and comparative mapping studies, respectively. Collectively, these data demonstrate a robust and flexible framework for functionally fine-mapping GWAS risk loci to identify translatable therapeutic targets.

PMID:37664640 | PMC:PMC10470213 | DOI:10.1016/j.isci.2023.107576

iScience. 2023 Aug 9;26(9):107591. doi: 10.1016/j.isci.2023.107591. eCollection 2023 Sep 15.

ABSTRACT

Personalized prediction is ideal in chronic lymphocytic leukemia (CLL). Although refined models have been developed, stratifying patients in risk groups, it is required to accommodate time-dependent information of patients, to address the clinical heterogeneity observed within these groups. In this direction, this study proposes a personalized stepwise dynamic predictive algorithm (PSDPA) for the time-to-first-treatment of the individual patient. The PSDPA introduces a personalized Score, reflecting the evolution in the patient's follow-up, employed to develop a reference pool of patients. Score evolution's similarity is used to predict, at a selected time point, the time-to-first-treatment for a new patient. Additional patient's biological information may be utilized. The algorithm was applied to 20 CLL patients, indicating that stricter assessment criteria for the Score evolution's similarity, and biological similarity exploitation, may improve prediction. The PSDPA capitalizes on both the follow-up and the biological background of the individual patient, dynamically promoting personalized prediction in CLL.

PMID:37664638 | PMC:PMC10470317 | DOI:10.1016/j.isci.2023.107591

iScience. 2023 Aug 9;26(9):107589. doi: 10.1016/j.isci.2023.107589. eCollection 2023 Sep 15.

ABSTRACT

The current TNM staging system for pancreatic ductal adenocarcinoma (PDAC) has revised the definitions of T and N categories as well as stage groups. However, studies validating these modifications have yielded inconsistent results. The existing TNM staging system in prognostic prediction remains unsatisfactory. The prognosis of PDAC is closely associated with pathological and biological factors. Herein, we propose a new staging system incorporating distant metastasis, postoperative serum levels of CA19-9 and CEA, tumor size, lymph node metastasis, lymphovascular involvement, and perineural invasion to enhance the accuracy of prognosis assessment. The proposed staging system exhibited a strong correlation with both overall survival and recurrence-free survival, effectively stratifying survival into five distinct tiers. Additionally, it had favorable discrimination and calibration. Thus, the proposed staging system demonstrates superior prognostic performance compared to the TNM staging system, and can serve as a valuable complementary tool to address the limitations of TNM staging in prognostication.

PMID:37664604 | PMC:PMC10469961 | DOI:10.1016/j.isci.2023.107589

iScience. 2023 Aug 9;26(9):107587. doi: 10.1016/j.isci.2023.107587. eCollection 2023 Sep 15.

ABSTRACT

Acute myocardial infarction dominates coronary artery disease mortality. Identifying bio-signatures for plaque destabilization and rupture is important for preventing the transition from coronary stability to instability and the occurrence of thrombosis events. This computational systems biology study enrolled 2,235 samples from 22 independent bulks cohorts and 14 samples from two single-cell cohorts. A machine-learning integrative program containing nine learners was developed to generate a warning classifier linked to atherosclerotic plaque vulnerability signature (APVS). The classifier displays the reliable performance and robustness for distinguishing ST-elevation myocardial infarction from chronic coronary syndrome at presentation, and revealed higher accuracy to 33 pathogenic biomarkers. We also developed an APVS-based quantification system (APVSLevel) for comprehensively quantifying atherosclerotic plaque vulnerability, empowering early-warning capabilities, and accurate assessment of atherosclerosis severity. It unraveled the multidimensional dysregulated mechanisms at high resolution. This study provides a potential tool for macro-level differential diagnosis and evaluation of subtle genetic pathological changes in atherosclerosis.

PMID:37664595 | PMC:PMC10470306 | DOI:10.1016/j.isci.2023.107587

iScience. 2023 Aug 9;26(9):107596. doi: 10.1016/j.isci.2023.107596. eCollection 2023 Sep 15.

ABSTRACT

Recent studies suggest that infection reprograms hematopoietic stem and progenitor cells (HSPCs) to enhance innate immune responses upon secondary infectious challenge, a process called "trained immunity." However, the specificity and cell types responsible for this response remain poorly defined. We established a model of trained immunity in mice in response to Mycobacterium avium infection. scRNA-seq analysis revealed that HSPCs activate interferon gamma-response genes heterogeneously upon primary challenge, while rare cell populations expand. Macrophages derived from trained HSPCs demonstrated enhanced bacterial killing and metabolism, and a single dose of recombinant interferon gamma exposure was sufficient to induce similar training. Mice transplanted with influenza-trained HSPCs displayed enhanced immunity against M. avium challenge and vice versa, demonstrating cross protection against antigenically distinct pathogens. Together, these results indicate that heterogeneous responses to infection by HSPCs can lead to long-term production of bone marrow derived macrophages with enhanced function and confer cross-protection against alternative pathogens.

PMID:37664586 | PMC:PMC10470378 | DOI:10.1016/j.isci.2023.107596

Front Cell Dev Biol. 2023 Aug 17;11:1254636. doi: 10.3389/fcell.2023.1254636. eCollection 2023.

NO ABSTRACT

PMID:37664459 | PMC:PMC10470824 | DOI:10.3389/fcell.2023.1254636

Mol Ther Nucleic Acids. 2023 Aug 24;33:813-815. doi: 10.1016/j.omtn.2023.08.008. eCollection 2023 Sep 12.

NO ABSTRACT

PMID:37662964 | PMC:PMC10474341 | DOI:10.1016/j.omtn.2023.08.008

Front Immunol. 2023 Aug 16;14:1240425. doi: 10.3389/fimmu.2023.1240425. eCollection 2023.

ABSTRACT

The bivalent mRNA vaccine is recommended to address coronavirus disease variants, with additional doses suggested for high-risk groups. However, the effectiveness, optimal frequency, and number of doses remain uncertain. In this study, we examined the long-term cellular and humoral immune responses following the fifth administration of the mRNA severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in patients undergoing hemodialysis. To our knowledge, this is the first study to monitor long-term data on humoral and cellular immunity dynamics in high-risk populations after five doses of mRNA vaccination, including the bivalent mRNA vaccine. Whereas most patients maintained humoral immunity throughout the observation period, we observed reduced cellular immune reactivity as measured by the ancestral-strain-stimulated ELISpot assay in a subset of patients. Half of the individuals (50%; 14/28) maintained cellular immunity three months after the fifth dose, despite acquiring humoral immunity. The absence of a relationship between positive controls and T-Spot reactivity suggests that these immune alterations were specific to SARS-CoV-2. In multivariable analysis, participants aged ≥70 years showed a marginally significant lower likelihood of having reactive results. Notably, among the 14 individuals who received heterologous vaccines, 13 successfully acquired cellular immunity, supporting the effectiveness of this administration strategy. These findings provide valuable insights for future vaccination strategies in vulnerable populations. However, further research is needed to evaluate the involvement of immune tolerance and exhaustion through repeated vaccination to optimize immunization strategies.

PMID:37662950 | PMC:PMC10469480 | DOI:10.3389/fimmu.2023.1240425

Front Genet. 2023 Aug 17;14:1213283. doi: 10.3389/fgene.2023.1213283. eCollection 2023.

ABSTRACT

We report a case of Klippel Trenaunay Syndrome that was monitored both clinically and molecularly over a period of 9 years. A somatic mosaic mutation of PIK3CA (p(E545G)) was identified using both cfDNA NGS liquid biopsy and tissue biopsy. At the age of 56, due to intervening clonal mutations in PIK3CA background, she developed a squamous cell carcinoma in the right affected leg which was treated surgically. Nine years later, lung bilateral adenocarcinoma arose on PIK3CA mutated tissues supported by different clonal mutations. One year later, the patient died from metastases led by a new FGFR3 clone unresponsive to standard-of-care, immunotherapy-based. Our results highlight the presence of a molecular hallmark underlying neoplastic transformation that occurs upon an angiodysplastic process and support the view that PIK3CA mutated tissues must be treated as precancerous lesions. Importantly, they remark the effectiveness of combining cfDNA NGS liquid and tissue biopsies to monitor disease evolution as well as to identify aggressive clones targetable by tailored therapy, which is more efficient than conventional protocols.

PMID:37662840 | PMC:PMC10469863 | DOI:10.3389/fgene.2023.1213283

Front Plant Sci. 2023 Aug 18;14:1232367. doi: 10.3389/fpls.2023.1232367. eCollection 2023.

ABSTRACT

The pathogenicity of intracellular plant pathogenic bacteria is associated with the action of pathogenicity factors/effectors, but their physiological roles for most phytoplasma species, including 'Candidiatus Phytoplasma solani' are unknown. Six putative pathogenicity factors/effectors from six different strains of 'Ca. P. solani' were selected by bioinformatic analysis. The way in which they manipulate the host cellular machinery was elucidated by analyzing Nicotiana benthamiana leaves after Agrobacterium-mediated transient transformation with the pathogenicity factor/effector constructs using confocal microscopy, pull-down, and co-immunoprecipitation, and enzyme assays. Candidate pathogenicity factors/effectors were shown to modulate plant carbohydrate metabolism and the ascorbate-glutathione cycle and to induce autophagosomes. PoStoSP06, PoStoSP13, and PoStoSP28 were localized in the nucleus and cytosol. The most active effector in the processes studied was PoStoSP06. PoStoSP18 was associated with an increase in phosphoglucomutase activity, whereas PoStoSP28, previously annotated as an antigenic membrane protein StAMP, specifically interacted with phosphoglucomutase. PoStoSP04 induced only the ascorbate-glutathione cycle along with other pathogenicity factors/effectors. Candidate pathogenicity factors/effectors were involved in reprogramming host carbohydrate metabolism in favor of phytoplasma own growth and infection. They were specifically associated with three distinct metabolic pathways leading to fructose-6-phosphate as an input substrate for glycolysis. The possible significance of autophagosome induction by PoStoSP28 is discussed.

PMID:37662165 | PMC:PMC10471893 | DOI:10.3389/fpls.2023.1232367

J Alzheimers Dis. 2023 Aug 25. doi: 10.3233/JAD-230548. Online ahead of print.

ABSTRACT

BACKGROUND: APOE is the largest genetic risk factor for Alzheimer's disease (AD), but there is a substantial polygenic component. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk across molecular processes and pathways that contribute to heterogeneity of disease presentation.

OBJECTIVE: We examined polygenic risk impacting specific AD-associated pathways and its relationship with clinical status and biomarkers of amyloid, tau, and neurodegeneration (A/T/N).

METHODS: We analyzed data from 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied pathway analysis and clustering to identify AD-associated "pathway clusters" and construct pathway-specific PRSs (excluding the APOE region). We tested associations with diagnostic status, abnormal levels of amyloid and ptau, and hippocampal volume.

RESULTS: Thirteen pathway clusters were identified, and eight pathway-specific PRSs were significantly associated with AD diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau-positivity was also associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs.

CONCLUSIONS: Pathway PRS may contribute to understanding separable disease processes, but do not add significant power for predictive purposes. These findings demonstrate that AD-phenotypes may be preferentially associated with risk in specific pathways, and defining genetic risk along multiple dimensions may clarify etiological heterogeneity in AD. This approach to delineate pathway-specific PRS can be used to study other complex diseases.

PMID:37661888 | DOI:10.3233/JAD-230548

J Alzheimers Dis. 2023 Aug 28. doi: 10.3233/JAD-230027. Online ahead of print.

ABSTRACT

BACKGROUND: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-β (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive.

OBJECTIVE: To disentangle the massive heterogeneities in Alzheimer's disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology.

METHODS: In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains.

RESULTS: Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development.

CONCLUSIONS: Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-β and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.

PMID:37661878 | DOI:10.3233/JAD-230027

Am J Clin Nutr. 2023 Sep;118(3):591-604. doi: 10.1016/j.ajcnut.2023.07.002. Epub 2023 Aug 8.

ABSTRACT

BACKGROUND: The capacity of an individual to respond to changes in food intake so that postprandial metabolic perturbations are resolved, and metabolism returns to its pre-prandial state, is called phenotypic flexibility. This ability may be a more important indicator of current health status than metabolic markers in a fasting state.

AIM: In this parallel randomized controlled trial study, an energy-restricted healthy diet and 2 dietary challenges were used to assess the effect of weight loss on phenotypic flexibility.

METHODS: Seventy-two volunteers with overweight and obesity underwent a 12-wk dietary intervention. The participants were randomized to a weight loss group (WLG) with 20% less energy intake or a weight-maintenance group (WMG). At weeks 1 and 12, participants were assessed for body composition by MRI. Concurrently, markers of metabolism and insulin sensitivity were obtained from the analysis of plasma metabolome during 2 different dietary challenges-an oral glucose tolerance test (OGTT) and a mixed-meal tolerance test.

RESULTS: Intended weight loss was achieved in the WLG (-5.6 kg, P < 0.0001) and induced a significant reduction in total and regional adipose tissue as well as ectopic fat in the liver. Amino acid-based markers of insulin action and resistance such as leucine and glutamate were reduced in the postprandial phase of the OGTT in the WLG by 11.5% and 28%, respectively, after body weight reduction. Weight loss correlated with the magnitude of changes in metabolic responses to dietary challenges. Large interindividual variation in metabolic responses to weight loss was observed.

CONCLUSION: Application of dietary challenges increased sensitivity to detect metabolic response to weight loss intervention. Large interindividual variation was observed across a wide range of measurements allowing the identification of distinct responses to the weight loss intervention and mechanistic insight into the metabolic response to weight loss.

PMID:37661105 | DOI:10.1016/j.ajcnut.2023.07.002

Neuroscience. 2023 Sep 1:S0306-4522(23)00407-4. doi: 10.1016/j.neuroscience.2023.08.038. Online ahead of print.

ABSTRACT

Fluvastatin (FLV), the first synthetically derived 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitor, is a potent inhibitor of cholesterol biosynthesis. While its primary mechanism of action is to reduce cholesterol levels, there is some evidence suggesting that it may also have effects on K+ channels. However, the overall effects of fluvastatin on ionic currents are not yet well understood. The whole-cell clamp recordings were applied to evaluate the ionic currents and action potentials of cells. Here, we have demonstrated that FLV can effectively inhibit the amplitude of erg-mediated K+ current (IK(erg)) in pituitary tumor (GH3) cells, with an IC50 of approximately 3.2 µM. In the presence of FLV, the midpoint in the activation curve of IK(erg) was distinctly shifted to a less negative potential by 10 mV, with minimal modification of the gating charge. However, the magnitude of hyperpolarization-activated cation current (Ih) elicited by long-lasting membrane hyperpolarization was progressively decreased, with an IC50 value of 8.7 µM, upon exposure to FLV. More interestingly, we also found that FLV (5 µM) could regulate the action potential and afterhyperpolarization properties in primary embryonic mouse cortical neurons. Our study presents compelling evidence indicating that FLV has the potential to impact both the amplitude and gating of the ion channels IK(erg) and Ih. We also provide credible evidence suggesting that this drug has the potential to modify the properties of action potentials and the afterhyperpolarization current in electrically excitable cells. However, the assumption that these findings translate to similar in-vivo results remains unclear.

PMID:37661016 | DOI:10.1016/j.neuroscience.2023.08.038

Biol Psychiatry. 2023 Sep 1:S0006-3223(23)01532-9. doi: 10.1016/j.biopsych.2023.08.020. Online ahead of print.

ABSTRACT

Knowledge of the microbiome-gut-brain axis has revolutionized the field of psychiatry. It is now well recognized that the gut bacteriome is associated with, and likely influences, the pathogenesis of mental disorders, including major depressive disorder and bipolar disorder. However, whilst substantial advances in the field of microbiome science have been made, we have likely only scratched the surface in our understanding of how these ecosystems might contribute to mental disorder pathophysiology. Beyond the gut bacteriome, research into lesser explored components of the gut microbiome, including the gut virome, mycobiome, archaeome, and parasitome, is increasingly suggesting relevance in psychiatry. The contribution of microbiomes beyond the gut, including the oral, lung, and small intestinal microbiomes, to human health and pathology should not be overlooked. Increasing both our awareness and understanding of these less traversed fields of research is critical to improving the therapeutic benefits of treatments targeting the gut microbiome, including fecal microbiome transplantation, postbiotics and biogenics, and dietary intervention. Interdisciplinary collaborations integrating systems biology approaches are required to fully elucidate how these different microbial components and distinct microbial niches interact with each other and their human hosts. Excitingly, we may be at the start of the next microbiome revolution, and thus one step closer to informing the field of precision psychiatry to improve outcomes for those living with mental illness.

PMID:37661007 | DOI:10.1016/j.biopsych.2023.08.020

J Biol Chem. 2023 Sep 1:105205. doi: 10.1016/j.jbc.2023.105205. Online ahead of print.

ABSTRACT

Inflammation is one of the vital mechanisms through which the immune system responds to harmful stimuli. During inflammation, pro and anti-inflammatory cytokines interplay to orchestrate fine-tuned, dynamic immune responses. The cytokine interplay governs switches in the inflammatory response and dictates the propagation and development of the inflammatory response. Molecular pathways underlying the interplay are complex, and time-resolved monitoring of mediators and cytokines is necessary as a basis to study them in detail. Our understanding can be advanced by mathematical models which enable to analyze the system of interactions and their dynamical interplay in detail. We, therefore, used a mathematical modeling approach to study the interplay between prominent pro and anti-inflammatory cytokines with a focus on tumor necrosis factor (TNF) and interleukin 10 (IL-10) in lipopolysaccharide (LPS)-primed primary human monocytes. Relevant time-resolved data were generated by experimentally adding or blocking IL-10 at different time points. The model was successfully trained and could predict independent validation data and was further used to perform simulations to disentangle the role of IL-10 feedbacks during an acute inflammatory event. We used the insight to obtain a reduced predictive model including only the necessary IL-10-mediated feedbacks. Finally, the validated reduced model was used to predict early IL-10 - TNF switches in the inflammatory response. Overall, we gained detailed insights into fine-tuning of inflammatory responses in human monocytes and present a model for further use in studying the complex and dynamic process of cytokine-regulated acute inflammation.

PMID:37660912 | DOI:10.1016/j.jbc.2023.105205

STAR Protoc. 2023 Sep 2;4(3):102533. doi: 10.1016/j.xpro.2023.102533. Online ahead of print.

ABSTRACT

Social isolation, a risk factor for mortality and various disease states, in mice remains poorly understood, due in part to under-consideration of housing temperature and the murine thermoneutral zone. Here, we present a housing protocol to minimize the confounding effect of chronic cold stress on socially isolated mice that are unable to socially thermoregulate. We describe steps for allocating mice to group housing or social isolation conditions, housing mice in thermoneutral cabinets, feeding mice with high-fat diet, and measuring body weight, food intake, and metabolic indicators. For complete details on the use and execution of this protocol, please refer to Queen et al..1.

PMID:37660300 | DOI:10.1016/j.xpro.2023.102533