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Your Blood is Out for Delivery: Considerations of Shipping Time and Temperature on Degradation of RNA from Stabilized Whole Blood.
No full textRemote research studies are an invaluable tool for reaching populations with limited access to large medical centers or universities. To expand the remote study toolkit, we previously developed homeRNA, which allows for at-home self-collection and stabilization of blood and demonstrated the feasibility of using homeRNA in high temperature climates. Here, we expand upon this work through a systematic study exploring the effects of high temperature on RNA integrity (represented as RNA Integrity Number, RIN) through in-lab and field experiments. Compared to the frozen controls (overall mean RIN of 8.2, n = 8), samples kept at 37 °C for 2, 4, and 8 days had mean RINs of 7.6, 5.9, and 5.2 (n = 3), respectively, indicating that typical shipping conditions (∼2 days) yield samples suitable for downstream RNA sequencing. Shorter time intervals (6 h) resulted in minimal RNA degradation (median RIN of 6.4, n = 3) even at higher temperatures (50 °C) compared to the frozen control (mean RIN of 7.8, n = 3). Additionally, we shipped homeRNA-stabilized blood from a single donor to 14 states and back during the summer with continuous temperature probes (7.1 median RIN, n = 42). Samples from all locations were analyzed with 3′ mRNA-seq to assess differences in gene counts, with the data suggesting that there was no preferential degradation of transcripts as a result of different shipping times, temperatures, and regions. Overall, our data support that homeRNA can be used in elevated temperature conditions, enabling decentralized sample collection for telemedicine, global health, and clinical research
Structures of ATP-binding cassette transporter ABCC1 reveal the molecular basis of cyclic dinucleotide cGAMP export.
No full textCyclic nucleotide GMP-AMP (cGAMP) plays a critical role in mediating the innate immune response through the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. Recent studies showed that ATP-binding cassette subfamily C member 1 (ABCC1) is a cGAMP exporter. The exported cGAMP can be imported into uninfected cells to stimulate a STING-mediated innate immune response. However, the molecular basis of cGAMP export mediated by ABCC1 remains unclear. Here, we report the cryoelectron microscopy (cryo-EM) structures of human ABCC1 in a ligand-free state and a cGAMP-bound state. These structures reveal that ABCC1 forms a homodimer via its N-terminal transmembrane domain. The ligand-bound structure shows that cGAMP is recognized by a positively charged pocket. Mutagenesis and functional studies confirmed the roles of the ligand-binding pocket in cGAMP recognition and export. This study provides insights into the structure and function of ABCC1 as a cGAMP exporter and lays a foundation for future research targeting ABCC1 in infection and anti-cancer immunity
Placental and Cord Blood DNA Methylation Changes Associated With Gestational Diabetes Mellitus in a Marginalized Population: The Untold Role of Saturated Fats.
Get PDFThe role of DNA methylation (DNAm) and its modulation by dietary factors in gestational diabetes mellitus (GDM) remains underexplored, particularly in marginalized populations. This study investigates DNAm alterations in GDM-exposed cord blood and placenta and their association with maternal dietary quality and single nutrient intake in a low-income population from the Myanmar-Thailand border. A matched case-control design (GDM: n = 38, controls: n = 34) was selected from a Myanmar-Thailand pregnancy cohort. Dietary intake was assessed via 24-h recalls and analyzed using Nutritionist Pro, with dietary quality evaluated by the healthy eating index (HEI). DNAm was profiled in 72 cord blood and 72 placental samples using the Infinium MethylationEPIC array. Significant differences in dietary vitamin D, total folate, and saturated fat intake were observed between the groups. RnBeads analyses revealed hypomethylation as the predominant DNAm pattern in GDM, particularly at ADORA2B (placenta) and ZFP57 (cord blood) promoters. The excessive intake of saturated fats was associated with GDM hypomethylation profiles and negatively correlated with ZFP57 methylation levels. This study highlights the influence of saturated fat intake on epigenetic changes in pregnancy, revealing potential biomarkers for GDM and emphasizing the need for tailored, population-specific nutritional interventions to mitigate transgenerational health impacts
Necrosis drives susceptibility to Mycobacterium tuberculosis in Polg(D257A) mutator mice
Get PDFThe genetic and molecular determinants that underlie the heterogeneity of Mycobacterium tuberculosis (Mtb) infection outcomes in humans are poorly understood. Multiple lines of evidence demonstrate that mitochondrial dysfunction can exacerbate mycobacterial disease severity, and mutations in some mitochondrial genes confer susceptibility to mycobacterial infection in humans. Here, we report that mutations in mitochondria DNA (mtDNA) polymerase gamma potentiate susceptibility to Mtb infection in mice. PolgD257A mutator mtDNA mice fail to mount a protective innate immune response at an early infection time point, evidenced by high bacterial burdens, reduced M1 macrophages, and excessive neutrophil infiltration in the lungs. Immunohis tochemistry reveals signs of enhanced necrosis in the lungs of Mtb-infected PolgD257A mice, and PolgD257A mutator macrophages are hypersusceptible to extrinsic triggers of necroptosis ex vivo. By assigning a role for mtDNA mutations in driving necrosis during Mtb infection, this work further highlights the requirement for mitochondrial homeosta sis in mounting balanced immune responses to Mtb
Innovative strategies for the discovery of new drugs against androgenetic alopecia.
No full textIntroduction
Androgenetic alopecia (AGA) is the most common cause of hair loss worldwide. The significant psychological and social impact of AGA continues to drive demand for more effective treatments beyond the limited options currently available. Areas covered
The authors review the key components of AGA pathogenesis, as well as current treatments, and therapeutic techniques under development. Innovative strategies for AGA drug discovery are still needed, given the significant unmet medical needs and the limited efficacy of both current and emerging treatments. The authors outline relevant preclinical models, such as hair follicle (HF) cell cultures, 3D spheroids, organoids, follicle explants, and animal models, highlighting their advantages and limitations in AGA research. Finally, they summarize the primary objectives in AGA treatment development, including direct hair growth promotion, interference with androgen signaling, and HF rejuvenation, identifying key pathogenesis intervention points for treatment development. Expert opinion
Developing better in vitro models, possibly using induced pluripotent stem cell (iPSC) systems, could greatly accelerate drug discovery. Similarly, a superior in vivo model could significantly expedite drug discovery. Near future development research should focus on drug delivery improvements. Longer term, treatments targeting AGA’s underlying pathophysiology and promoting HF rejuvenation or true regeneration would provide the most benefit to prospective patients. Plain Language Summary
Androgenetic alopecia (AGA), typically called male/female pattern baldness, is the most common type of hair loss worldwide. It is caused by the action of androgen hormones targeting cells in hair follicles and causing them to age prematurely and eventually die off. AGA can have a significant negative psychological and social impact on those affected. Current treatments are limited, often not very effective, and carry the risk of side effects, leading to a demand for better therapeutic options by both patients and clinicians.
This article reviews the key factors that cause AGA, existing treatments, and new therapies being developed. The authors discuss different laboratory models used to study AGA, like cultures of hair follicle cells, 3D cell clusters (called spheroids and organoids), whole hair follicles and scalp skin donated by volunteers, and animal models of hair growth and alopecia. The authors highlight the strengths and weaknesses of the models to help researchers select the ones most suitable for their drug development studies. They also outline the main goals in developing new AGA treatments: namely directly promoting hair growth, blocking the effects of androgens, or rejuvenating damaged hair follicles.
The authors suggest that creating better lab models, possibly using induced pluripotent stem cells (iPSCs), could speed up drug discovery for AGA. Improving how drugs are delivered to the scalp could help in the near future. In the longer term, treatments that address the underlying causes of AGA, restoring hair follicle size and increasing scalp hair follicle density, would be most beneficial for patients
Predicting the impact of rare variants on RNA splicing in CAGI6.
Get PDFVariants which disrupt splicing are a frequent cause of rare disease that have been under-ascertained clinically. Accurate and efficient methods to predict a variant\u27s impact on splicing are needed to interpret the growing number of variants of unknown significance (VUS) identified by exome and genome sequencing. Here, we present the results of the CAGI6 Splicing VUS challenge, which invited predictions of the splicing impact of 56 variants ascertained clinically and functionally validated to determine splicing impact. The performance of 12 prediction methods, along with SpliceAI and CADD, was compared on the 56 functionally validated variants. The maximum accuracy achieved was 82% from two different approaches, one weighting SpliceAI scores by minor allele frequency, and one applying the recently published Splicing Prediction Pipeline (SPiP). SPiP performed optimally in terms of sensitivity, while an ensemble method combining multiple prediction tools and information from databases exceeded all others for specificity. Several challenge methods equalled or exceeded the performance of SpliceAI, with ultimate choice of prediction method likely to depend on experimental or clinical aims. One quarter of the variants were incorrectly predicted by at least 50% of the methods, highlighting the need for further improvements to splicing prediction methods for successful clinical application
Analysis of functional connectivity changes from childhood to old age: A study using HCP-D, HCP-YA, and HCP-A datasets.
Get PDFWe present a new clustering-enabled regression approach to investigate how functional connectivity (FC) of the entire brain changes from childhood to old age. By applying this method to resting-state functional magnetic resonance imaging data aggregated from three Human Connectome Project studies, we cluster brain regions that undergo identical age-related changes in FC and reveal diverse patterns of these changes for different region clusters. While most brain connections between pairs of regions show minimal yet statistically significant FC changes with age, only a tiny proportion of connections exhibit practically significant age-related changes in FC. Among these connections, FC between region clusters from the same functional network tends to decrease over time, whereas FC between region clusters from different networks demonstrates various patterns of age-related changes. Moreover, our research uncovers sex-specific trends in FC changes. Females show much higher FC mainly within the default mode network, whereas males display higher FC across several more brain networks. These findings underscore the complexity and heterogeneity of FC changes in the brain throughout the lifespan
Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments.
Get PDFThe tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then verify CISA\u27s applicability across data modalities with melanoma histocytometry whole slide images, revealing that T-cell:macrophage synapse formation correlates with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types
Impact of essential genes on the success of genome editing experiments generating 3313 new genetically engineered mouse lines.
Get PDFThe International Mouse Phenotyping Consortium (IMPC) systematically produces and phenotypes mouse lines with presumptive null mutations to provide insight into gene function. The IMPC now uses the programmable RNA-guided nuclease Cas9 for its increased capacity and flexibility to efficiently generate null alleles in the C57BL/6N strain. In addition to being a valuable novel and accessible research resource, the production of 3313 knockout mouse lines using comparable protocols provides a rich dataset to analyze experimental and biological variables affecting in vivo gene engineering with Cas9. Mouse line production has two critical steps - generation of founders with the desired allele and germline transmission (GLT) of that allele from founders to offspring. A systematic evaluation of the variables impacting success rates identified gene essentiality as the primary factor influencing successful production of null alleles. Collectively, our findings provide best practice recommendations for using Cas9 to generate alleles in mouse essential genes, many of which are orthologs of genes linked to human disease
