Biology subjects

Andersen, R.

Publications and source records attributed to Andersen, R..

5 recordsLinked to original sources

bioRxiv2025

Recovery of microbial ecophysiology and carbon accrual functions in peatlands under restoration

Peatlands are water-logged ecosystems that limit microbial decomposition making them effective carbon sinks. However, drainage or erosion removes these constraints on decomposition, switching them to carbon sources. Restoration aims to reverse these trends. Microbial ecophysiology influences carbon fluxes but how it responds to peatland degradation and restoration is poorly understood. Here we used metagenomics to study microbial functions and quantified growth rates using isotope labelling across seven sites in Britain, each with restored, degraded, and near-natural peatlands. We found that growth rates in restored treatments were comparable to the near-natural, but were significantly higher in degraded. This growth rate reduction in restored peatlands was dependent on the scale of degradation and the length of restoration, and was underpinned by a shift towards energetically less favourable metabolic pathways such as anaerobic respiration, fermentation, and carbon fixation. A peatland ecosystem health index estimated based on measurements of peat moisture, oxygen, pH, organic matter chemistry, and moss cover, explained a significant amount of variation in microbial ecophysiology across the gradient. We demonstrate that microbial ecophysiology changes with peatland ecosystem health in a predictable manner. This knowledge can inform restoration targets and monitoring of recovery to maximise the return of carbon accrual functions of peatlands.

microbiology↗

bioRxiv2025

Cell-type-specific patterns and consequences of somatic mutation in development and aging brain

Elucidating the role of somatic mutations in cancer, healthy tissues, and aging depends on methods that can accurately characterize somatic mosaicism across different cell types, as well as assay their impact on cellular function. Current technologies to study cell-type-specific somatic mutations within tissues are low-throughput. We developed Duplex-Multiome, incorporating duplex consensus sequencing to accurately identify somatic single-nucleotide variants (sSNV) from the same nucleus simultaneously analyzed for single-nucleus ATAC-seq (snATAC-seq) and RNA-seq (snRNA-seq). By introducing strand-tagging into the construction of snATAC-seq libraries, duplex sequencing reduces sequencing error by >10,000-fold while eliminating artifactual mutational signatures. When applied to 98%/2% mixed cell lines, Duplex-Multiome identified sSNVs present in 2% of cells with 92% precision and accurately captured known sSNV mutational spectra, while revealing unexpected subclonal lineages. Duplex-Multiome of > 51,400 nuclei from postmortem brain tissue captured sSNV burdens and spectra across all major brain cell types and subtypes, including those difficult to assay by single-cell whole-genome sequencing (scWGS). This revealed for the first time that diverse neuronal and glial cell types show distinct rates and patterns of age-related mutation, while also directly discovering developmental cell lineage relationships. Duplex-Multiome identified clonal sSNVs occurring at increased rates in glia of certain aged brains, as well as clonal sSNVs that correlated with changes in expression of nearby genes, in both neurotypical and autism spectrum disorder (ASD) individuals, directly demonstrating that somatic mutagenesis can contribute to gene expression phenotypes. Duplex-Multiome can be easily adopted into the 10X Multiome protocol and will bridge somatic mosaicism to a wide range of phenotypic readouts across cell types and tissues.

genomics↗

bioRxiv2025

Autism-Associated Genes and Neighboring lncRNAs Converge on Key Gene Regulatory Networks

Autism spectrum disorder (ASD) is highly heritable, and mutations in hundreds of genes have been implicated as individually rare causes of ASD1-3. Understanding how disruptions to these functionally diverse genes lead to the core features of ASD remains a major challenge4. Moreover, ASD is three- to four-fold more common in males than females5, and autistic females tend to carry more autosomal risk alleles for ASD compared to autistic males6,7, but the biological basis of this "female protective effect" (FPE) is unknown8,9. Here we show that individual perturbations of 18 ASD genes in human neural progenitor cells converge on shared effects on gene expression, including widespread downregulation of other ASD genes. De novo reconstruction of a gene regulatory network (GRN) enabled the identification of central transcriptional regulators, including the prominent ASD gene CHD8 as well as novel candidates such as REST, that drive this transcriptomic convergence. Furthermore, the X-linked transcription factor ZFX, which is expressed from both the active and the inactive X chromosomes in females10, emerged as a key activator of many ASD genes: we propose that the higher ZFX expression level observed in female brain can buffer damaging mutations in diverse ASD genes, contributing to the FPE. Together, these results reveal how key GRNs can become broadly and similarly dysregulated upon disruption of individual ASD genes and provide molecular insight into the female protective effect in ASD.

genetics↗

bioRxiv2023

Neural subspaces of imagined movements in parietal cortex remain stable over several years in humans.

A crucial goal in brain-machine interfacing is long-term stability of neural decoding performance, ideally without regular retraining. Here we demonstrate stable neural decoding over several years in two human participants, achieved by latent subspace alignment of multi-unit intracortical recordings in posterior parietal cortex. These results can be practically applied to significantly expand the longevity and generalizability of future movement decoding devices.

neuroscience↗

bioRxiv2023

Neural representations of economic decision variables in human posterior parietal cortex

Decision making has been intensively studied in the posterior parietal cortex in non-human primates on a single neuron level. In humans decision making has mainly been studied with psychophysical tools or with fMRI. Here, we investigated how single neurons from human posterior parietal cortex represent numeric values informing future decisions during a complex two-player game. The tetraplegic study participant was implanted with a Utah electrode array in the anterior intraparietal area (AIP). We played a simplified variant of Black Jack with the participant while neuronal data was recorded. During the game two players are presented with numbers which are added up. Each time a number is presented the player has to decide to proceed or to stop. Once the first player stops or the score reaches a limit the turn passes on to the second player who tries to beat the score of the first player. Whoever is closer to the limit (without overshooting) wins the game. We found that many AIP neurons selectively responded to the face value of the presented number. Other neurons tracked the cumulative score or were selectively active for the upcoming decision of the study participant. Interestingly, some cells also kept track of the opponents score. Our findings show that parietal regions engaged in hand action control also represent numbers and their complex transformations. This is also the first demonstration of complex economic decisions being possible to track in single neuron activity in human AIP. Our findings show how tight are the links between parietal neural circuits underlying hand control, numerical cognition and complex decision-making.

neuroscience↗