A system of reporters for comparative investigation of EJC-independent and EJC-enhanced nonsense-mediated mRNA decay.

Nonsense-mediated mRNA decay (NMD) is a network of pathways that degrades transcripts that undergo premature translation termination. In mammals, NMD can be divided into the exon junction complex (EJC)-enhanced and EJC-independent branches. Fluorescence- and luminescence-based reporters have long been effective tools to investigate NMD, yet existing reporters largely focus on the EJC-enhanced pathway. Here, we present a system of reporters for comparative studies of EJC-independent and EJC-enhanced NMD. This system also enables the study of NMD-associated outcomes such as premature termination codon (PTC) readthrough and truncated protein degradation. These reporters are compatible with fluorescence or luminescence-based readouts via transient transfection or stable integration. Using this reporter system, we show that EJC-enhanced NMD RNA levels are reduced by 2- or 9-fold and protein levels are reduced by 7- or 12-fold compared to EJC-independent NMD, depending on the reporter gene used. Additionally, the extent of readthrough induced by G418 and an NMD inhibitor (SMG1i), alone and in combination, varies across NMD substrates. When combined, G418 and SMG1i increase readthrough product levels in an additive manner for EJC-independent reporters, while EJC-enhanced reporters show a synergistic effect. We present these reporters as a valuable toolkit to deepen our understanding of NMD and its associated mechanisms.

The heterogeneous wound microbiome varies with wound care pain, dressing type, and inflammatory gene expression.

Wound dressing changes are essential procedures for wound management. However, ~50% of patients experience severe pain during these procedures despite the availability of analgesic medications, indicating a need for novel therapeutics that address underlying causes of pain. Along with other clinical factors, wound pathogens and inflammatory immune responses have previously been implicated in wound pain. To test whether these factors could contribute to severe pain during wound dressing changes, we conducted an exploratory, cross-sectional analysis of patient-reported pain, inflammatory immune responses, and wound microbiome composition in 445 wounds at the time of a study dressing change. We profiled the bacterial composition of 406 wounds using 16S ribosomal RNA amplicon sequencing and quantified gene expression of 13 inflammatory markers in wound fluid using quantitative real-time polymerase chain reaction (qPCR). Neither inflammatory gene expression nor clinically observed inflammation were associated with severe pain, but Corynebacterium and Streptococcus were of lower relative abundance in wounds of patients reporting severe pain than those reporting little or no pain. Wound microbiome composition differed by wound location, and correlated with six of the inflammatory markers, including complement receptor C5AR1, pro-inflammatory cytokine interleukin (IL)1ß, chemokine IL-8, matrix metalloproteinase MMP2, and the antimicrobial peptide encoding cathelicidin antimicrobial peptide. Interestingly, we found a relationship between the wound microbiome and vacuum-assisted wound closure (VAC). These findings identify preliminary, associative relationships between wound microbiota and host factors which motivate future investigation into the directional relationships between wound care pain, wound closure technologies, and the wound microbiome.

Feeding Behaviors in Infants and Toddlers Later Diagnosed with Autism Spectrum Disorder: A Systematic Review.

Children with autism spectrum disorder (ASD) are five times more likely to have feeding difficulties than neurotypical peers, although the majority of evidence describes feeding difficulty in children age 2 years and older. The purpose of this study is to systematically review the literature on feeding characteristics of children age 0-24 months who were later diagnosed with ASD with an emphasis on the measurement tools used to assess these feeding behaviors. We conducted a systematic review of the literature using PRISMA guidelines. Using selected keywords, a search was conducted using PubMed, PsycINFO, and CINAHL databases for relevant articles to identify feeding characteristics in infants and toddlers (age 0-24 months) later diagnosed with ASD. Sixteen studies were selected for this review by two independent reviewers. Among the selected studies, feeding difficulties were reported in all infant oral feeding modalities (breastfeeding, bottle feeding, and complementary feeding) by infants later diagnosed with ASD. However, the evidence was conflicting among studies regarding feeding characteristics, such as sucking differences while breastfeeding, use of the spoon with feedings, and preference of solid food texture, that presented in infants later diagnosed with ASD. A lack of consistent measurement of feeding behaviors in infants later diagnosed with ASD contributes to the difficulty in comparison across studies. Future research should focus on developing targeted, validated instruments for measuring feeding difficulty in this population with emphasis on breastfeeding and bottle feeding difficulty.

Forecasting climate-associated non-tuberculous mycobacteria (NTM) infections in the UK using international surveillance data and machine learning.

Nontuberculous mycobacteria (NTM) cause skin and lung infections, have high mortality rates, and are resistant to a range of antibiotics and water treatment methods. As NTM reside in environmental reservoirs, they are sensitive to environmental conditions. The suitability of their environmental reservoirs can increase as a result of climate change, subsequently increasing environmental exposure and infection rates. NTM infections are not generally notifiable, including in the UK, but sustained increases have been observed in regions that report NTM infection rates. To assess the burden of NTM infections in the UK under projected climate change, we examined the relationship between climate variables and available NTM surveillance data internationally. Statistically significant increases were found in regions where NTM infections are notifiable, which were positively associated with increased precipitation and temperatures. A random forest regressor was trained using supervised learning from international NTM surveillance data and linked climate variables. The random forest model was applied to UK climate projections, projecting a 6.2% increase in NTM infection rates over the next 10 years, with notable regional variation. Our random forest model predicts that the forecasted impacts of climate change in the UK, including increasing temperatures and frequency of heavy rainfall, will lead to increases in NTM infection rates. Robust surveillance in the future is necessary to increase data available to train models, increasing our predictive power in forecasting climate-associated NTM trends. Our results highlight a novel aspect of how climate change will impact health outcomes in the UK.

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery.

BACKGROUND: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma. METHODS: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony. FINDINGS: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively. INTERPRETATION: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted. FUNDING: Cancer Research UK, Blood Cancer UK, National Institute for Health Research.

Systematic analysis of nonsense variants uncovers peptide release rate as a novel modifier of nonsense-mediated mRNA decay efficiency.

Nonsense variants underlie many genetic diseases. The phenotypic impact of nonsense variants is determined by Nonsense-mediated mRNA decay (NMD), which degrades transcripts with premature termination codons (PTCs). NMD activity varies across transcripts and cellular contexts via poorly understood mechanisms. Here, by leveraging human genetic datasets, we uncover that the amino acid preceding the PTC dramatically affects NMD activity in human cells. We find that glycine codons in particular support high levels of NMD and are enriched before PTCs but depleted before normal termination codons (NTCs). Gly-PTC enrichment is most pronounced in human genes that tolerate loss-of-function variants. This suggests a strong biological impact for Gly-PTC in ensuring robust elimination of potentially toxic truncated proteins from non-essential genes. Biochemical assays revealed that the peptide release rate during translation termination is highly dependent on the identity of the amino acid preceding the stop codon. This release rate is the most critical feature determining NMD activity across our massively parallel reporter assays. Together, we conclude that NMD activity is significantly modulated by the "window of opportunity" offered by translation termination kinetics. Integrating the window of opportunity model with the existing framework of NMD would enable more accurate nonsense variant interpretation in the clinic.

Alcaligenes faecalis corrects aberrant matrix metalloproteinase expression to promote reepithelialization of diabetic wounds.

Chronic wounds are a common and costly complication of diabetes, where multifactorial defects contribute to dysregulated skin repair, inflammation, tissue damage, and infection. We previously showed that aspects of the diabetic foot ulcer microbiota were correlated with poor healing outcomes, but many microbial species recovered remain uninvestigated with respect to wound healing. Here, we focused on Alcaligenes faecalis, a Gram-negative bacterium that is frequently recovered from chronic wounds but rarely causes infection. Treatment of diabetic wounds with A. faecalis accelerated healing during early stages. We investigated the underlying mechanisms and found that A. faecalis treatment promotes reepithelialization of diabetic keratinocytes, a process that is necessary for healing but deficient in chronic wounds. Overexpression of matrix metalloproteinases in diabetes contributes to failed epithelialization, and we found that A. faecalis treatment balances this overexpression to allow proper healing. This work uncovers a mechanism of bacterial-driven wound repair and provides a foundation for the development of microbiota-based wound interventions.

Molecular Subtypes of High-Grade Serous Ovarian Cancer across Racial Groups and Gene Expression Platforms.

BACKGROUND: High-grade serous carcinoma (HGSC) gene expression subtypes are associated with differential survival. We characterized HGSC gene expression in Black individuals and considered whether gene expression differences by self-identified race may contribute to poorer HGSC survival among Black versus White individuals. METHODS: We included newly generated RNA sequencing data from Black and White individuals and array-based genotyping data from four existing studies of White and Japanese individuals. We used K-means clustering, a method with no predefined number of clusters or dataset-specific features, to assign subtypes. Cluster- and dataset-specific gene expression patterns were summarized by moderated t-scores. We compared cluster-specific gene expression patterns across datasets by calculating the correlation between the summarized vectors of moderated t-scores. After mapping to The Cancer Genome Atlas-derived HGSC subtypes, we used Cox proportional hazards models to estimate subtype-specific survival by dataset. RESULTS: Cluster-specific gene expression was similar across gene expression platforms and racial groups. Comparing the Black population with the White and Japanese populations, the immunoreactive subtype was more common (39% vs. 23%-28%) and the differentiated subtype was less common (7% vs. 22%-31%). Patterns of subtype-specific survival were similar between the Black and White populations with RNA sequencing data; compared with mesenchymal cases, the risk of death was similar for proliferative and differentiated cases and suggestively lower for immunoreactive cases [Black population HR = 0.79 (0.55, 1.13); White population HR = 0.86 (0.62, 1.19)]. CONCLUSIONS: Although the prevalence of HGSC subtypes varied by race, subtype-specific survival was similar. IMPACT: HGSC subtypes can be consistently assigned across platforms and self-identified racial groups.