Biology subjects

Karlsson, A.

Publications and source records attributed to Karlsson, A..

16 recordsLinked to original sources

bioRxiv2026

Dog-human gene network colocalization links synaptic signalling and ubiquitination to compulsive disorders

Obsessive-compulsive disorder (OCD) is highly polygenic, and the largest genome-wide association study (GWAS), with 53,660 cases and 2,044,417 controls, identified only 30 loci, a small fraction of loci estimated to explain its heritability - too few to resolve biological pathways. Pet dogs develop a compulsive disorder (dogCD) similar to OCD. In a GWAS of dogCD with 2,584 dogs from the community science project Darwin's Ark, each dog locus explains at least 40-fold more phenotypic variance than each human OCD locus, giving power equivalent to the human GWAS with 80-fold fewer individuals. Combining the two GWAS identifies a 165-gene network undetectable in humans at current sample sizes. This network is enriched for genes expressed in neurons, particularly in the amygdala and cortex, and comprises four biological processes: excitatory-inhibitory synaptic transmission, axon guidance and neuron recognition, protein ubiquitination, and adenylyl cyclase-activating G-protein-coupled receptor signaling. Like most complex human traits, dogCD risk is likely driven by regulatory variation: fine-mapped dogCD SNPs are non-coding, and dogCD loci are enriched in candidate cis-regulatory elements (cCREs) in a new dog epigenomic atlas spanning eight brain regions. The cross-species network implicates an inherited risk architecture largely outside current OCD pharmacotherapy, and establishes pet dogs as a model for gene network discovery, particularly for conditions underpowered in human studies.

genetics↗

bioRxiv2026

A single nuclei expression resource for exploring dog brain cell transcriptomic diversity

Domesticated dogs present a unique case in nature where mutualism with and selective breeding by humans has led to profound changes in their environment, physiology, and behaviour compared to their wolf-like ancestors. Dog tameness, sociability, and trainability have likely evolved due to significant alterations to brain function. Exploring the effects of domestication on the dog brain will be facilitated by the characterisation of dog brain cell diversity, a task which is not yet complete. To fill this gap, we use single-nucleus RNA sequencing and survey cell types across the dog brain. We present transcriptomes from almost 60,000 cells sampled from the cerebellum, thalamus, and three regions of the cerebrum. Our analysis identified 24 major clusters representing 21 broad cell types, and 131 subclusters revealing regional variation. Comparisons with human and mouse datasets revealed a high level of conservation in neurons across mammalian brains, and greater divergence in glial cells, particularly oligodendrocytes. We demonstrate the utility of the dataset for interrogating specific gene expression patterns across the brain, including genes implicated in dog domestication, behavioural traits, and disease. We discover distinct differences in the expression of opioid receptors in the brains of dogs, compared to humans and mice, providing a potential explanation for dogs' higher tolerance and lower risk of severe adverse effects of opioid drugs. The data from this project are released via a web application for use by the wider community.

genomics↗

bioRxiv2026

Identifying Novel Targets of the Stringent Response in Plants and Cyanobacteria using chemoproteomics

Survival in dynamic environments requires photosynthetic organisms to rapidly sense and respond to stress. The stringent response, mediated by the signaling molecule guanosine-3,5-bisdiphosphate (ppGpp), is crucial for acclimation to environmental changes such as darkness and nitrogen limitation. While it has been extensively characterized in heterotrophic bacteria such as Escherichia coli, the molecular mechanisms and regulatory targets of ppGpp in photosynthetic organisms remain less understood. Here, we report large-scale chemoproteomic identification of ppGpp-binding proteins across plant chloroplasts and cyanobacteria, revealing both conserved and novel targets compared to E. coli. In plants, we found that ppGpp regulates pyrimidine metabolism by inhibiting the chloroplastic enzyme aspartate transcarbamoylase (PyrB). In cyanobacteria, we found that ppGpp activates glucose-1-phosphate adenylyltransferase (GlgC) involved in glycogen synthesis, activates citrate synthase (GltA), and induces carboxysome aggregation. These findings expand the known ppGpp regulatory network in photosynthetic organisms and provide a foundation for understanding how ppGpp coordinates adaptation to nutrient and environmental stresses.

systems biology↗

bioRxiv2026

Multi-omics uncovers interaction in the vaginal microbiome and a type II secretion/Tad pilus system in Gardnerella vaginalis

The vaginal microbiome is a critical determinant of womens health. We investigated the genetic basis of common vaginal microbiome species and their biofilm formation. Genomic analysis of Gardnerella vaginalis (Gv) revealed a fundamental phylogenetic split correlating with high- versus low-biofilm phenotypes, driven by clade-specific genomic islands and allelic variants. In a dual-species coculture model of five key vaginal bacteria, Gv achieved numerical dominance, triggering extensive, asymmetric proteomic reprogramming in partner species while showing limited shifts itself. Proteins from biofilm-associated modules showed functional divergence, supported by AI-predicted structural variations in a type II secretion/Tad pilus system, which is first discovered from Gv strains. Integrated metabolomics identified a methyl-{beta}-carboline compound that is elevated in cocultures containing Prevotella bivia (Pb). This compound acts as a potent and selective inhibitor of Gv and Pb biofilms, sparing Lactobacillus crispatus. This work establishes a direct genomic basis for Gv virulence and demonstrates how interspecies interactions govern community dynamics and antimicrobial metabolite production. HighlightsO_LIComprehensive genomic resource comparing with high-quality long-read whole genomes and reference Gardnerella vaginalis and Lactobacillus iners strains. C_LIO_LIIntegrated multi-omics and functional analysis on the most common vaginal microbiome species using 16S rRNA gene sequencing, proteomics, metabolomics, and in vitro assays. C_LIO_LIKey phenotypes quantified, including biofilm formation and polymicrobial interactions. C_LIO_LIConserved Type II Secretion/Tad Pilus System identified across all Gardnerella vaginalis strains, with AI-predicted structural modeling. C_LIO_LIEvaluation of growth inhibition using metabolites against a panel of relevant microbes, including vaginal microbes and opportunistic pathogens. C_LI

microbiology↗

bioRxiv2026

Expression landscape of heterologous enzymes in Synechocystis sp. PCC 6803

Photosynthetic cyanobacteria are promising platforms for sustainable chemical production, as they can convert light and CO2 into valuable compounds. Achieving this often requires engineering cyanobacteria with non-native enzymes with strong promoters to maximize enzyme accumulation. However, despite extensive engineering efforts, the extent to which these enzymes misfold and undergo degradation in cyanobacteria remains unknown. Here, we systematically investigate the fate of recombinant proteins in Synechocystis sp. PCC 6803 by estimating protein loss due to protease degradation. To do this, we developed a quantitative approach that combines split-GFP reporting with inducible CRISPRi knockdown of Clp protease system, enabling estimation of portion of proteins that would otherwise be degraded. Applying this method to 103 heterologous proteins previously used in cyanobacterial metabolic engineering studies, we find that, on average, one-third of recombinant protein accumulation is lost to degradation, with some enzymes exhibiting more than 95% protein loss. Furthermore, we compare expression from identical expression constructs in E. coli and Synechocystis and find broad similarities in their protein accumulation patterns. Together, these findings provide the first quantitative overview of heterologous protein expression in cyanobacteria and identify enzymes that are suboptimal for their respective pathways, information usable to increase production titers in photosynthetic cell factories.

synthetic biology↗

bioRxiv2024

Activation and signaling characteristics of the hydroxy-carboxylic acid 3 receptor identified in human neutrophils through a microfluidic flow cell technique

Human neutrophils express numerous G protein-coupled receptors (GPCRs) of importance for immune regulation. Several of the functionally known neutrophil GPCRs, are not part of the human neutrophil proteome. To identify GPCRs not earlier shown to be expressed in human neutrophils, we utilized a microfluidic flow cell technique in combination with subcellular granule fractionation and liquid chromatography-tandem mass spectrometry (LC-MS/MS). This approach added the hydroxy-carboxylic acid 3 receptor (HCA3R) to the human neutrophil proteome. The {beta}-oxidation intermediate 3-hydroxy-octanoic acid (3-OH-C8) is the primary endogenous agonist for this receptor which is highly expressed in adipocytes where it has anti-lipolytic effects. Literature describing the role and function of HCA3R in human neutrophils is scarce. We now show that 3-OH-C8 as well the synthetic HCA3R agonist IBC 293 activate human neutrophils determined as an increase in the intracellular concentration of free calcium ions ([Ca2+]i) and activation of the NADPH oxidase. However, in contrast to the rise in [Ca2+]i which could be triggered in naive neutrophils, pre-treatment of neutrophils was required for HCA3Rs to activate the NADPH oxidase. That is, the HCA3R-mediated NADPH oxidase activation occurred only in neutrophils pre-treated with either an actin cytoskeleton disrupter or an allosteric modulator targeting the GPCR termed free fatty acid receptor 2 (FFA2R). Our findings demonstrate that HCA3R is not only a new member of the human neutrophil proteome, but also exhibits functional activity with complex signaling pathways when stimulated with endogenous and synthetic HCA3R agonists.

immunology↗

bioRxiv2024

GENE THERAPY PREVENTS HEPATIC MITOCHONDRIAL DYSFUNCTION IN MURINE DEOXYGUANOSINE KINASE DEFICIENCY

Primary mitochondrial disorders are an uncommon cause of neonatal hepatic failure. Biallelic pathogenic variants of the gene encoding the mitochondrial localising enzyme deoxyguanosine kinase (DGUOK) cause hepatocerebral mitochondrial DNA depletion syndrome leading to acute neonatal liver failure and early mortality. There are currently no effective disease-modifying therapies. In this study, we developed an adeno-associated virus 9 (AAV9) gene therapy approach to treat a mouse model of DGUOK deficiency that recapitulates human disease. We delivered AAV9-hDGUOK gene therapy intravenously to newborn Dguok knock-out mice and showed that liver dysfunction was prevented in a dose dependent manner. Unexpectedly for neonatal delivery, durable and long-lasting liver transduction and RNA expression were demonstrated. Liver mitochondrial DNA depletion, deficiencies of oxidative phosphorylation complexes I, III and IV and liver transaminitis and survival were ameliorated in a dose-dependent manner.

genetics↗

bioRxiv2024

Multi-omic profiling of squamous cell lung cancer identifies metabolites and related genes associated with squamous cell carcinoma

BackgroundSquamous cell lung carcinoma (SqCC) is the second most common histological subtype of lung cancer. Besides -tumor-initiating and promoting DNA, RNA, and epigenetic alterations, aberrant tumor cell metabolism has been identified as one of the hallmarks of carcinogenesis. The aim of the current study was to identify SqCC-specific metabolites and key gene regulators that could eventually be used as new anticancer targets. MethodsTranscriptional (n=156), proteomics (n=118), and mass spectrometry-based metabolomic data (n=73) were gathered for a cohort of resected early-stage lung cancers representing all major histological subgroups. SqCC-specific differentially expressed genes were integrated with proteogenomic and metabolic data using genome scale metabolic models (GEMs). Findings were validated in cohorts of tumors, normal specimens, and cancer cell lines. In situ protein expression of SLC6A8 was investigated in 213 tumors. ResultsDifferential gene expression analysis identified 280 SqCC-specific genes, of which 57 were connected to metabolites through GEMs. Metabolic profiling identified 7 SqCC-specific metabolites, of which increased creatine and decreased phosphocholine levels matched to SqCC-specific elevated expression of SLC6A8 and decreased expression of CHKA, part of respective GEMs. Expression of both genes appeared tumor cell-associated, and in particular the elevated expression of SLC6A8 identified SqCC also in stage IV disease. ConclusionElevated creatine levels and the overexpression of its transporter protein SLC6A8 appear as a distinct metabolic feature of SqCC. Considering ongoing clinical trials focused on SLC6A8 inhibition in other malignancies, exploring SLC6A8 inhibition in SqCC appears motivated based on a metabolic addiction hypothesis.

cancer biology↗

bioRxiv2024

Chloroplastic ascorbate acts as a regulatory hub in plant metabolism regardless of oxidative stress

Ascorbate is a major plant metabolite that plays crucial roles in various processes, from reactive oxygen scavenging to epigenetic regulation. However, to what extent and how ascorbate modulates metabolism is largely unknown. To address this, we investigated the consequences of chloroplastic and total cellular ascorbate-deficiencies by studying chloroplastic ascorbate-transporter pht4;4 mutant lines, and the ascorbate-deficient vtc2-4 mutant of Arabidopsis thaliana. Under regular growth conditions, both ascorbate-deficiencies caused minor alterations in photosynthesis, with no apparent signs of oxidative damage. In contrast, metabolomics analysis revealed a global and largely overlapping metabolome rewiring in both ascorbate-deficiencies, suggesting that chloroplastic ascorbate modulates plant metabolism. We observed significant alterations in amino acid metabolism, particularly in arginine metabolism, activation of nucleotide salvage pathways, and changes in secondary metabolism. In addition, proteome-wide analysis of thermostability revealed that ascorbate may interact with enzymes involved in arginine metabolism, the Calvin-Benson cycle, and several photosynthetic electron transport components. Overall, our results suggest that, independently of oxidative stress, chloroplastic ascorbate interconnects and coordinates diverse metabolic pathways in vascular plants and thus acts as a regulatory hub.

plant biology↗

bioRxiv2022

The role of redox-cofactor regeneration and ammonium assimilation in secretion of amino acids as byproducts of Clostridium thermocellum

Clostridium thermocellum is a cellulolytic thermophile considered for consolidated bioprocessing of lignocellulose to ethanol. Improvements in ethanol yield are required for industrial implementation, but incompletely understood causes of amino acid secretion impede progress. In this study, amino acid secretion was investigated by gene deletions in ammonium-regulated NADPH-supplying and -consuming pathways and physiological characterization in cellobiose- or ammonium-limited chemostats. First, the contribution of the NADPH-supplying malate shunt was studied with strains using either the NADPH-yielding malate shunt ({Delta}ppdk) or redox-independent conversion of PEP to pyruvate ({Delta}ppdk {Delta}malE::Peno-pyk). In the latter, branched-chain amino acids, especially valine, were significantly reduced, whereas the ethanol yield increased 46-60%, suggesting that secretion of these amino acids balances NADPH surplus from the malate shunt. Unchanged amino acid secretion in {Delta}ppdk falsified a previous hypothesis on ammonium-regulated PEP-to-pyruvate flux redistribution. Possible involvement of another NADPH-supplier, namely NADH-dependent reduced ferredoxin:NADP+ oxidoreductase (nfnAB), was also excluded. Finally, deletion of glutamate synthase (gogat) in ammonium assimilation resulted in upregulation of NADPH-linked glutamate dehydrogenase activity and decreased amino acid yields. Since gogat in C. thermocellum is putatively annotated as ferredoxin-linked, which is supported by product redistribution observed in this study, this deletion likely replaced ferredoxin with NADPH in ammonium assimilation. Overall, these findings indicate that a need to reoxidize NADPH is driving the observed amino acid secretion, likely at the expense of NADH needed for ethanol formation. This suggests that metabolic engineering strategies on simplifying redox metabolism and ammonium assimilation can contribute to increased ethanol yields. ImportanceImproving the ethanol yield of C. thermocellum is important for industrial implementation of this microorganism in consolidated bioprocessing. A central role of NADPH in driving amino acid byproduct formation was demonstrated, by eliminating the NADPH-supplying malate shunt and separately by changing the cofactor specificity in ammonium assimilation. With amino acid secretion diverting carbon and electrons away from ethanol, these insights are important for further metabolic engineering to reach industrial requirements on ethanol yield. This study also provides chemostat data relevant for training genome-scale metabolic models and improving the validity of their predictions, especially considering the reduced degree-of-freedom in redox metabolism of the strains generated here. In addition, this study advances fundamental understanding on mechanisms underlying amino acid secretion in cellulolytic Clostridia as well as regulation and cofactor specificity in ammonium assimilation. Together, these efforts aid development of C. thermocellum for sustainable consolidated bioprocessing of lignocellulose to ethanol with minimal pretreatment.

bioengineering↗

bioRxiv2021

Influenza viral particles harboring the SARS-CoV-2 spike RBD as a combination respiratory disease vaccine

Vaccines targeting SARS-CoV-2 have gained emergency FDA approval, however the breadth against emerging variants and the longevity of protection remains unknown. Post-immunization boosting may be required, perhaps on an annual basis if the virus becomes an endemic pathogen. Seasonal influenza virus vaccines are already developed every year, an undertaking made possible by a robust global vaccine production and distribution infrastructure. To create a seasonal combination vaccine targeting influenza viruses and SARS-CoV-2 that is also amenable to frequent reformulation, we have developed a recombinant influenza A virus (IAV) genetic platform that "reprograms" the virus to package an immunogenic domain of the SARS-CoV-2 spike (S) protein onto IAV particles. Vaccination with this combination vaccine elicits neutralizing antibodies and provides protection from lethal challenge with both pathogens. This technology may allow for leveraging of established influenza vaccine infrastructure to generate a cost-effective and scalable seasonal vaccine solution for both influenza and coronaviruses.

microbiology↗

bioRxiv2020

Reference ontology and database annotation of the COVID-19 Open Research Dataset (CORD-19)

The COVID-19 Open Research Dataset (CORD-19) was released in March 2020 to allow the machine learning and wider research community to develop techniques to answer scientific questions on COVID-19. The dataset consists of a large collection of scientific literature, including over 100,000 full text papers. Annotating training data to normalise variability in biological entities can improve the performance of downstream analysis and interpretation. To facilitate and enhance the use of the CORD-19 data in these applications, in late March 2020 we performed a comprehensive annotation process using named entity recognition tool, TERMite, along with a number of large reference ontologies and vocabularies including domains of genes, proteins, drugs and virus strains. The additional annotation has identified and tagged over 45 million entities within the corpus made up of 62,746 unique biomedical entities. The latest updated version of the annotated data, as well as older versions, is made openly available under GPL-2.0 License for the community to use at: https://github.com/SciBiteLabs/CORD19

immunology↗

bioRxiv2020

Optimising biomedical relationship extraction with BioBERT: Best practices for data creation

Text mining is widely used within the life sciences as an evidence stream for inferring relationships between biological entities. In most cases, conventional string matching is used to identify cooccurrences of given entities within sentences. This limits the utility of text mining results, as they tend to contain significant noise due to weak inclusion criteria. We show that, in the indicative case of protein-protein interactions (PPIs), the majority of sentences containing cooccurrences ({bsim}75%) do not describe any causal relationship. We further demonstrate the feasibility of fine tuning a strong domain-specific language model, BioBERT, to analyse sentences containing cooccurrences and accurately (F1 score: 88.95%) identify functional links between proteins. These strong results come in spite of the deep complexity of the language involved, which limits the accuracy even of expert curators. We establish guidelines for best practices in data creation to this end, including an examination of inter-annotator agreement, of semisupervision, and of rules based alternatives to manual curation, and explore the potential for downstream use of the model to accelerate curation of interactions in the SIGNOR database of causal protein interactions and the IntAct database of experimental evidence for physical protein interactions.

bioinformatics↗

bioRxiv2020

A new long-read dog assembly uncovers thousands of exons and functional elements missing in the previous reference

Here we present a new high-quality canine reference genome with gap number reduced 41-fold, from 23,836 to 585. Analysis of existing and novel data, RNA-seq, miRNA-seq and ATAC-seq, revealed a large proportion of these harboured previously hidden elements, including genes, promoters and miRNAs. Short-read dark regions were detected, and genomic regions completed, including the DLA, TCR and 366 cancer genes. 10x sequencing of 27 dogs uncovered a total of 22.1 million SNPs, Indels and larger structural variants (SVs). 1.4% overlap with protein coding genes and could provide a source of normal or aberrant phenotypic modifications.

genomics↗

bioRxiv2019

Core-2 O-glycans are required for Galectin-3 interaction with the osteoarthritis related protein lubricin

Synovial fluid lubricin (proteoglycan 4) is a mucin-type O-linked glycosylated (60% of the mass) biological lubricant involved in osteoarthritis (OA) development. Lubricin has been reported to be cross-linked by synovial galectin-3 on the lubricating articular surface. Here, we confirm that binding to galectin-3 depended on core-2 O-linked glycans, where surface plasmon resonance of a recombinant lubricin (rhPRG4) devoid of core-2 structures lacked binding capacity to recombinant galectin-3. Both galectin-3 levels and interactions with synovial lubricin were found to be decreased in late-stage OA patients coinciding with an increase of truncated and less sialylated core 1 O-glycans. These data suggest a defect cross-linking of surface active molecules in OA and provides novel insights into OA molecular pathology.

biochemistry↗

bioRxiv2018

A natural history model for planning prostate cancer testing: calibration and validation using Swedish registry data

Recent prostate cancer screening trials have given conflicting results and it is unclear how to reduce prostate cancer mortality while minimising overdiagnosis and overtreatment. Prostate cancer testing is a partially observable process, and planning for testing requires either extrapolation from randomised controlled trials or, more flexibly, modelling of the cancer natural history.\n\nAn existing US prostate cancer natural history model (Gulati et al, Biostatistics 2010;11:707-719) did not model for differences in survival between Gleason 6 and 7 cancers and predicted too few Gleason 7 cancers for contemporary Sweden. We re-implemented and re-calibrated the US model to Sweden. We extended the model to more finely describe the disease states, their time to biopsy-detectable cancer and prostate cancer survival. We first calibrated the model to the incidence rate ratio observed in the European Randomised Study of Screening for Prostate Cancer (ERSPC) together with age-specific cancer staging observed in the Stockholm PSA (prostate-specific antigen) and Biopsy Register; we then calibrated age-specific survival by disease states under contemporary testing and treatment using the Swedish National Prostate Cancer Register.\n\nAfter calibration, we were able to closely match observed prostate cancer incidence trends in Sweden. Assuming that patients detected at an earlier stage by screening receive a commensurate survival improvement, we find that the calibrated model replicates the observed mortality reduction in a simulation of ERSPC.\n\nUsing the resulting model, we predicted incidence and mortality following the introduction of regular testing. Compared with a model of the current testing pattern, organised 8 yearly testing for men aged 55-69 years was predicted to reduce prostate cancer incidence by 0.11% with no increase in the mortality rate. The model is open source and suitable for planning for effective prostate cancer screening into the future.\n\nAuthor summaryA naive perspective is that cancer screening is simple: people are screened, some cancers are detected early, and cancer mortality rates decline. However, the mathematics for screening becomes difficult quickly, it is hard to infer causation from observational data, and even large randomised screening studies provide limited evidence. Simulations are therefore important for planning cancer screening.\n\nWe found an older US prostate cancer natural history model to be poorly suited for contemporary Sweden. We therefore re-implemented and re-calibrated the US model using data from Swedish registries.\n\nOur revised model, the Stockholm \"Prostata\" model, provides predictions similar to those observed in the detailed Swedish registers on prostate cancer incidence and mortality. By modelling the mechanisms of the screening effect, we can predict the benefits and harms under a range of screening interventions.

epidemiology↗