Biology subjects

Wist, J.

Publications and source records attributed to Wist, J..

6 recordsLinked to original sources

bioRxiv2026

A dependency-free, streamable format and cross-language toolkit for scalable LC-MS feature detection: reading only what you need

Mass spectrometry generates data faster than it can be read, and the exchange standard, mzML, is text-based and must be parsed in full before any spectrum is accessible. Binary alternatives are smaller but depend on storage engines such as HDF5, so access is dictated by the engine, not the file. We present Ionic (.ion), an open-source, compact, streamable binary format, and Quant{middle dot}ion, a processing toolkit built on the former. Ionic stores spectra, chromatograms and metadata as independently compressed, indexed blocks, so a reader retrieves only the bytes it needs, even inside a web browser, and converts losslessly to and from mzML. Ionic was smaller than compressed mzMLb on every acquisition type tested, and extracting one compound took under 40 ms, 35 to 90 times faster than an mzML reader. Quant{middle dot}ion exposes one core to R, Python, and JavaScript with identical results, and recovered 97% of true features on a ground-truth benchmark.

bioinformatics↗

bioRxiv2026

Multi-Omic Dissection of Autism Reveals Dominant Effects of Family, Sex, and Host-Microbe Metabolic Interactions

Autism spectrum disorder (ASD) has been associated with gut microbiome and metabolic alterations, but reported biomarkers are inconsistent and often inadequately account for family and shared environment. We analysed 620 children, including 334 with ASD and 286 neurotypical siblings, with a median age of 6.0 years (IQR 4.0-8.0). Faecal and urine samples were collected monthly up to eight times. After quality control, 869 microbiome, 754 faecal metabolome and 787 urine metabolome samples were analysed using 16S rRNA sequencing, NMR and LC-MS metabolomics. Mixed models accounted for family, repeated sampling and biological sex. Family membership explained 46.1% of variation across microbiome and metabolome profiles, compared with 8.0% attributable to ASD. After family adjustment, ASD explained only 0.1% to 0.3% of microbiome beta diversity. No stable taxonomic biomarkers were identified, and microbial classification was poor (AUROC <0.75). Urinary metabolomics identified elevated 5-hydroxy-L-tryptophan and altered phenylalanine metabolism. Structural equation modelling found no direct associations between selected taxa and metabolites. These findings argue against a universal ASD microbiome and indicate that family context contributes more strongly than diagnosis to microbial and metabolic variation.

microbiology↗

bioRxiv2026

Postprandial profiling of the duodenal microbiome reveals the impact of food structure and association with luminal metabolite and gut hormone responses

The human duodenum harbours a complex, dynamic microbial community that is challenging to study due to inaccessibility, particularly postprandially when nutrient-rich chyme and fluctuating metabolites create unique microbial niches. We used naso-duodenal intubation to longitudinally sample duodenal luminal contents following pea-based meals of differing food structure, alongside parallel blood collection. Shotgun metagenomic sequencing, comprehensive metabolomic profiling and gut hormone measurements were combined to explore microbe-metabolite-hormone interactions. Food structure significantly affected postprandial bacterial composition, with saccharolytic oral taxa increasing after meals with intact structure. Alpha diversity was influenced by structure type (P = 0.025), with whole pea seeds promoting greater diversity than pea flour. Network analysis revealed complex interactions between the duodenal microbiome, luminal metabolites and gut hormones, with most microbial associations linked to glucose-dependent insulinotropic polypeptide (GIP) rather than glucagon-like peptide-1 (GLP-1). Metabolic profiling showed meal-dependent changes in amino acid metabolism, including shifts in D/L amino acid ratios over time consistent with microbial metabolism. The duodenal microbiome showed close phylogenetic relationships with the oral microbiome, with composition influenced by food structuring and swallowing. These findings reveal dynamic microbe-metabolite interplay in the human duodenum during digestion and its relationship to gut hormone responses.

microbiology↗

bioRxiv2025

Dried Blood Spot Lipidomics in Diabetes

Comprehensive lipidomic profiling in diabetes has identified disease-associated lipid signatures that may support more personalised monitoring beyond routine glycaemic control. Dried blood spot (DBS) microsampling offers a minimally invasive method for collecting and storing small blood volumes (<50 {micro}L), enabling decentralised and longitudinal sampling. However, its application in lipidomics for cardiometabolic phenotyping remains underexplored. In this study, 34 participants (17 diabetics, 17 non-diabetic controls) self-collected DBS samples using advanced microsampling devices (10 {micro}L, Capitainer(R)B). Lipid extracts were analysed using a validated liquid chromatography-trapped ion mobility-time-of-flight mass spectrometry method optimised for semi-quantitative DBS lipidomics. Multivariate analysis revealed significant differences in lipidomic profiles (n = 432 lipids) between diabetic and non-diabetic individuals (R{superscript 2}Y = 0.82, Q{superscript 2}Y = 0.50, p = 0.05). Key discriminatory lipids (all VIP > 1.44), including HexCer(18:1;O2/24:0), HexCer(18:1;O2/22:0), LPC(16:0), PC(O-34:3), TG(18:0_18:1_20:3), and TG(18:1_18:1_22:6), were consistent with matched venous and capillary plasma samples. Lipid class and structural differences, including elevated long-chain triacylglycerols and reduced lysophosphatidylcholines reflected known dyslipidaemia in diabetes and demonstrate the capacity of DBS to capture biologically meaningful lipid perturbations. Participant-reported outcomes from Problem Areas In Diabetes (PAID-20), Patient Activation Measure (PAM-13), and microsampling perception questionnaires highlighted psychosocial and behavioural insights, and indicated strong support for DBS sampling over venepuncture, citing ease of use and reduced burden. These findings establish DBS lipidomics as a feasible and informative approach for stratifying cardiometabolic disease, supporting broader implementation in remote, personalised monitoring frameworks (Figure 1). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/656742v1_fig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@c53b4org.highwire.dtl.DTLVardef@14b507forg.highwire.dtl.DTLVardef@191e563org.highwire.dtl.DTLVardef@16af172_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Graphical abstract - Chapter 5. C_FIG

biochemistry↗

bioRxiv2023

Clinical prediction of wound re-epithelisation outcomes in non-severe burn injury using the plasma lipidome

Whilst wound repair in severe burns has received substantial research attention, non-severe burns (<20% total body surface area) remain relatively understudied, despite causing considerable physiological impact and constituting most of the hospital admissions for burns. Early prediction of healing outcomes would decrease financial and patient burden, and aid in preventing long-term complications from poor wound healing. Lipids have been implicated in inflammation and tissue repair and may play essential roles in burn wound healing. In this study, plasma samples were collected from 20 non-severe burn patients over 6 weeks from admission, including surgery, and analysed by liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance spectroscopy to detect 850 lipids and 112 lipoproteins. Orthogonal projections to latent structures-discriminant analysis was performed to identify changes associated with re-epithelialisation and delayed re-epithelisation. We demonstrated that the lipid and lipoprotein profiles at admission could predict re-epithelisation outcomes at 2 weeks post-surgery, and that these discriminatory profiles were maintained up to 6 weeks post-burn. Inflammatory markers GlycB and C-reactive protein indicated divergent systemic responses to the burn injury at admission. Triacylglycerols, diacylglycerols and low-density lipoprotein subfractions were associated with delayed wound closure (p-value <0.02, Cliffs delta >0.7), whilst high-density lipoprotein subfractions, phosphatidylinositols, phosphatidylcholines, and phosphatidylserines were associated with re-epithelisation at 2 weeks post-surgery (p-value <0.01, Cliffs delta <-0.7). Further model validation will potentially lead to personalised intervention strategies to reduce the risk of chronic complications post-burn injury.

systems biology↗

bioRxiv2023

Metabolic consequences of non-severe burn injury are associated with increased plasma markers of inflammation and cardiovascular disease risk.

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic co-morbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on impact of non-severe injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of non-severe burn injury, longitudinal plasma was collected from adults (n=35) who presented at hospital with a non-severe burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from non-burn control participants (n=14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoproteins signatures and 852 lipid species from across 20 subclasses. Multivariate data modelling (Orthogonal projection to latent structures-discriminate analysis) revealed alterations in lipoprotein and lipid metabolism when comparing baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value <1.0e-4), low density lipoprotein-2 subfractions (Variable importance in projection score; VIP >6.83e-1) and monoacyglyceride (20:4)(p-value <1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP >7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of non-severe burn injury. The phenotype is indicative of an acute inflammatory profile which continues to be sustained post-injury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have elevated incidence post-burn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalise intervention strategies and improve acute care, reducing risk of chronic co-morbidity.

systems biology↗