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Hansen, L.

Publications and source records attributed to Hansen, L..

At least 19 recordsLinked to original sources

Genome-resolved ecology and evolution of the microbiome enabled by quantitative long-read metagenomics

Standard metagenomics resolves microbial communities only in relative terms and at coarse taxonomic resolution, obscuring how individual strains change in absolute abundance and evolve within a host. We present long-read quantiomics (LRQ), a quantitative metagenomics platform coupling long-read sequencing with plasmid-based internal standards to recover high-quality genomes, including from degraded or low-input stool, and measure absolute, genome-resolved strain abundances. We validate LRQ using large plasmid standards and bacterial spike-ins, then apply it to eight years of dense sampling from an individual with colonic Crohn's disease. LRQ resolves co-resident strains of the same species following opposing trajectories with inflammation. Escherichia coli, long treated as a single pathobiont, separates into two sub-populations with opposing inflammation responses; the inflammation-associated lineage carries an immune-evasion module of virulence-associated metal-acquisition, biofilm, capsule and toxin genes. We observe genome-wide adaptive sweeps on timescales matched to disease incidence. LRQ therefore converts long-read metagenomics from a genome-recovery tool into a quantitative framework providing absolute, strain-level measurement of microbial ecology and evolution.

microbiology↗

Predatory bacteria impact C. elegans life-history traits by modulating microbiota community dynamics and thereby vitamin B12 availability

Predatory bacteria such as Bdellovibrio are emerging as ecological modulators in microbial communities by restructuring community composition, yet their roles in host-associated microbiomes remain poorly understood. Using Caenorhabditis elegans as model host and its defined microbiota, we investigated how two Bdellovibrio strains with distinct prey ranges (B. tiberii MYbb2 and B. krueschi MYbb4) affect microbial community composition and host life-history traits. Both strains consistently altered microbiome composition, with MYbb4 causing more pronounced alpha-diversity shifts and MYbb2 selectively enriching strains of the genus Ochrobactrum which coincided with higher host median lifespan. Genome-based predictions indicate that de novo vitamin B12 synthesis by Ochrobactrum underlies the observed host phenotype, which was confirmed through quantitative measurements of the vitamin in mono-cell cultures. Employing the acdh-1p::GFP transcriptional reporter strain, we confirmed that a diet of B12-producing bacteria suppresses the B12-independent propionate detoxification pathway in the host, demonstrating that bacterially produced B12 is bioavailable to C. elegans. Exogenous B12 supplementation assays further confirmed the lifespan-extending effect. Together, these results suggest that predation-driven enrichment of B12-producing bacteria maintains B12 levels sufficient to detoxify propionyl-CoA via the B12-dependent pathway, preventing the accumulation of toxic metabolic byproducts that would otherwise arise under B12-limiting conditions and reduce host lifespan. Our findings demonstrate that predatory bacteria are important drivers of microbiome structure with direct consequences for host physiology, representing an underappreciated ecological mechanism for microbiome modulation.

ecology↗

Neat1 alleviates ischemic injury in skeletal muscles

Peripheral artery disease (PAD) has historically been regarded as an age-related vascular disorder; however, recent attention has shifted toward the myopathic components of the disease. Conventional interventions, such as revascularization, have had limited success in reversing muscle pathology or preventing adverse outcomes like amputation. Hypoxia-inducible factors (HIFs) are key regulators of cellular responses to ischemia, including the promotion of angiogenesis and glycolysis. While pharmacological stabilization of HIF proteins represents a promising therapeutic strategy, its efficacy is diminished in aged muscles due to their intrinsically low basal HIF expression. We hypothesized that long noncoding RNAs (lncRNAs) might enhance the hypoxic response in aged muscle through post-transcriptional regulation of HIF expression. Our study identified a long noncoding RNA Neat1, as a critical mediator of the hypoxia-induced stress response, including upregulation of Hif1. In a murine hindlimb ischemia model, Neat1 knockout mice exhibited extensive necrosis following femoral artery ligation, whereas Neat1 overexpression conferred protection against ischemic injury. Mechanistically, we found that Neat1 regulates the stability of Hif1a mRNA, as Hif1a transcript levels were significantly reduced in Neat1-deficient muscle cells. Importantly, aged muscles displayed a blunted hypoxic response due to diminished Hif1a expression--an effect that was reversed through Neat1 overexpression, resulting in improved resistance to ischemic damage. In summary, our findings highlight Neat1 as a novel regulator of muscle adaptation to hypoxia in aging. Enhancing Neat1 expression may represent a promising therapeutic strategy for improving ischemic outcomes in patients with peripheral artery disease.

cell biology↗

A missense variant in PAOX in American Staffordshire Terriers with juvenile-onset polyneuropathy

Hereditary polyneuropathies in dogs mirror many features of human Charcot-Marie-Tooth (CMT) disease and offer valuable spontaneous models for discovery of genes variants involved in this disorder. A juvenile-onset polyneuropathy (JOP) in American Staffordshire Terriers (ASTs) resembles CMT, with motor and sensory deficits, often accompanied by laryngeal paralysis. To identify the underlying genetic cause, we conducted a genome-wide association study (GWAS) with 24 affected and 53 control ASTs that identified a significant locus at the distal end of chromosome 28. Homozygosity mapping analysis further defined a critical interval spanning 11 protein-coding genes and whole-genome sequencing revealed a missense variant in the PAOX gene encoding polyamine oxidase (NC_049249.1:g.41474541G>A), leading to a glycine-to-arginine substitution at a highly conserved residue, XP_038435135.1:p.(Gly382Arg). Genotypes at this variant were homozygous alternate in 96% of the affected dogs (n=53) and either homozygous reference or heterozygous in 336 unaffected ASTs; the mutant allele was not detected in any of 2519 genomes of other dog breeds. In silico predictions consistently supported its pathogenicity, and structural modeling suggested altered substrate binding. Although PAOX expression was preserved, proteomic profiling in affected nerve tissue revealed reduced levels of myelin-associated proteins, as well as dysregulation of mitochondrial and proteasomal pathways. Our findings establish this PAOX missense variant as the likely cause of JOP in ASTs and highlight the breed as a valuable large-animal model for studying inherited peripheral neuropathies. These results expand the spectrum of genes implicated in polyneuropathies and provide a basis for genetic testing and informed breeding strategies in ASTs. Author summaryWe studied a hereditary peripheral nerve disorder in American Staffordshire Terriers characterized by exercise intolerance, coordination problems, general weakness and difficulty breathing due to laryngeal paralysis. These signs closely resemble a group of inherited diseases in people known as Charcot-Marie-Tooth disease. To understand the genetic basis of this condition in dogs, we analyzed the genomes of affected and healthy individuals. Our research led us to a single gene, PAOX, which carries a missense variant likely affecting the function of polyamine oxidase and ultimately disrupting how the nerve cells function and survive. Most affected dogs had two copies of the mutant allele, while it was absent or in only one copy in healthy dogs. Additional analyses suggested that the variant may interfere with the nerves ability to maintain their structure and function properly. The mutant allele does not appear to reduce the overall level of PAOX protein, but it may affect how the protein works. Our findings provide a new genetic test that can help breeders avoid producing affected puppies. They also highlight this condition in dogs as a valuable model for understanding similar diseases in humans.

genetics↗

Capture, Confine, Characterize: High-Throughput Dielectrophoresis-Based Single-Cell Microfluidics Platform to Analyze Mammalian and Yeast Cells Using Raman Spectroscopy

Single-cell analysis technologies are pivotal in unraveling complex biological mechanisms, yet existing platforms are often limited to sequencing-based end-point measurements, which fail to capture live cell dynamics. Here, we present a microfluidic- microelectronic device, the Microfluidic dielectrophoretic Arresting System (MiDAS) that employs dielectrophoresis (DEP) for high-throughput single-cell and droplet trapping in a compact array. We tested multiple trap geometries, including a 20 m-diameter DEP trap for polymer microbeads, fungal and mammalian cells, and a 40 m-diameter trap for water-in-oil droplets. The platform demonstrates broad sample compatibility, reliably immobilizing cells and beads of varying sizes. By integrating optical imaging and Raman spectroscopy, we enable rapid, non-destructive interrogation of individual cells with temporal resolution. We describe different modes of MiDAS operation to trap and manipulate single-cells or reverse emulsion droplets on demand, with applications in droplet microfluidics. Our MiDAS platforms simple fabrication, robust performance, and broad compatibility with diverse sample types position it as a versatile tool with transformative potential for single-cell analysis, offering researchers an innovative approach to interrogate cellular dynamics with unprecedented precision and throughput.

bioengineering↗

A Multi-Organ Murine Metabolomics Atlas Reveals Molecular Dysregulations in Alzheimer's Disease

The etiology of Alzheimers Disease (AD) remains largely unclear but is likely driven by gene-environment interactions. Here, we present a multi-organ untargeted metabolomics dataset (2,271 samples) generated from five tissue types in two genetic AD mouse models under colonized or germ-free conditions, complemented by shotgun metagenomics sequencing data (666 samples). Systems-level analyses of 3xTg and 5xFAD mice reveal clusters of dysregulated molecular classes across tissues including carnitines, bile acids, B vitamins, and neurotransmitters. This signature, coupled with microbiome profiles, suggests increased oxidative stress via mitochondrial dysfunction. Molecular feature tracking via tissueMASST, a mass spectrometry search tool we developed to bridge animal model findings with human data, identifies microbially-modulated phenylacetyl-carnitine as positively associated with aging and cognitive impairment across human AD studies. With hundreds of yet-to-be-characterized metabolites, this public resource and its associated tools will aid future research in the pathophysiology of AD.

microbiology↗

Empirically establishing drug exposure records directly from untargeted metabolomics data

Despite extensive efforts, extracting information on medication exposure from clinical records remains challenging. To complement this approach, we developed the tandem mass spectrometry (MS/MS) based GNPS Drug Library. This resource integrates MS/MS data for drugs and their metabolites/analogs with controlled vocabularies on exposure sources, pharmacologic classes, therapeutic indications, and mechanisms of action. It enables direct analysis of drug exposure and metabolism from untargeted metabolomics data independent of clinical records. Our library facilitates stratification of individuals in clinical studies based on the empirically detected medications, exemplified by drug-dependent microbiota-derived N-acyl lipid changes in a cohort with human immunodeficiency virus. The GNPS Drug Library holds potential for broader applications in drug discovery and precision medicine.

bioinformatics↗

Impact assessment and indigenous rights: Cumulative impact assessment of forestry on winter pastures in Mudusjävri reindeer herding co-operative in Finland

Assessing the cumulative effects of competing land uses on traditional indigenous livelihoods and culture is a critical component of ensuring the protection of indigenous peoples rights. Lack of appropriate methodologies for conducting cumulative impact assessment is a major concern in Sami indigenous communities across Sapmi, the traditional Sami territory covering the northern parts of Finland, Sweden, Norway and parts of north-western Russia. We report from a project in which a new type of GIS based impact assessment methodology was developed to assess effects of forestry on winter pastures of the Mudusjavri reindeer herding co-operative in northern Finland. Winter pasture quality was studied as a function of cumulative impacts from forestry. The aim was to develop a way to measure the level of harm caused by forestry on Sami culture and rights that are protected by national laws and international conventions - in order to assess whether the threshold for significant and hence unacceptable impact has been exceeded. An existing static model for lichen - the main natural winter fodder for reindeer - both for its biomass and growth was used along with mapped forest data to simulate the impacts of forestry on reindeer herding. Our assessment shows that the intensive industrial loggings that started in the 1950s have reduced the ground lichen biomass in Mudusjavris pastures by over 30% by 2020. The yearly lichen production has been reduced by 23 - 31% and the yearly lichen depending on the model version used. The respective cost of forestry for Mudusjavri reindeer herding is approximately 370 - 530 000 {euro}/year which is approximately half of the total turnover of the co-operative. Thus, our study indicates that significant harm has been caused on Sami reindeer herding by other land uses and especially forestry.

ecology↗

Circulating miR-126-3p is a mechanistic biomarker for knee osteoarthritis

As a chronic joint disease, osteoarthritis (OA) is a major contributor to pain and disability worldwide, and yet there are currently no validated soluble biomarkers or disease-modifying treatments. Since microRNAs are promising mechanistic biomarkers that can be therapeutically targeted, we aimed to prioritize reproducible circulating microRNAs in knee OA. We performed secondary analysis on two microRNA-sequencing datasets and found circulating miR-126-3p to be elevated in radiographic knee OA compared to non-OA individuals. This finding was validated in an independent cohort (N=145), where miR-126-3p showed an area under the receiver operating characteristic curve of 0.91 for distinguishing knee OA. Measuring miR-126-3p in six primary human knee OA tissues, subchondral bone, fat pad and synovium exhibited the highest levels, and cartilage the lowest. Following systemic miR-126-3p mimic treatment in a surgical mouse model of knee OA, we found reduced disease severity. Following miR-126-3p mimic treatment in human knee OA tissue explants, we found direct inhibition of genes associated with angiogenesis and indirect inhibition of genes associated with osteogenesis, adipogenesis, and synovitis. These findings suggest miR-126-3p becomes elevated during knee OA and mitigates disease processes to attenuate severity.

molecular biology↗

Context-dependence of T-loop mediated long-range RNA tertiary interactions

The architecture and folding of complex RNAs is governed by a limited set of highly recurrent structural motifs that form long-range tertiary interactions. One of these motifs is the T-loop, which was first identified in tRNA but is broadly distributed across biological RNAs. While the T-loop has been examined in detail in different biological contexts, the various receptors that it interacts with are not as well defined. In this study, we use a cell-based genetic screen in concert with bioinformatic analysis to examine three different, but related, T-loop receptor motifs found in the flavin mononucleotide (FMN) and cobalamin (Cbl) riboswitches. As a host for different T-loop receptors, we employed the env8 class-II Cbl riboswitch, an RNA that uses two T-loop motifs for both folding and supporting the ligand binding pocket. A set of libraries was created in which select nucleotides that participate in the T-loop/T-loop receptor (TL/TLR) interaction were fully randomized. Library members were screened for their ability to support Cbl-dependent expression of a reporter gene. While T-loops appear to be variable in sequence, we find that the functional sequence space is more restricted in the Cbl riboswitch, suggesting that TL/TLR interactions are context dependent. Our data reveal clear sequence signatures for the different types of receptor motifs that align with phylogenic analysis of these motifs in the FMN and Cbl riboswitches. Finally, our data suggest the functional contribution of various nucleobase-mediated long-range interactions within the riboswitch subclass of TL/TLR interactions that are distinct from those found in other RNAs. HighlightsO_LIThe T-loop motif frequently mediates tertiary interactions in RNA C_LIO_LIActivity-based screen used to explore T-loop mediate interactions in riboswitches C_LIO_LIResults from the screen were consistent with phylogenetic analysis C_LIO_LIT-loop/T-loop recepto{-}{-}{-}{-}r interactions are context dependent C_LI

biochemistry↗

A Generalizable Speech Emotion Recognition Model Reveals Depression and Remission

ObjectiveAffective disorders are associated with atypical voice patterns; however, automated voice analyses suffer from small sample sizes and untested generalizability on external data. We investigated a generalizable approach to aid clinical evaluation of depression and remission from voice using transfer learning: we train machine learning models on easily accessible non-clinical datasets and test them on novel clinical data in a different language. MethodsA Mixture-of-Experts machine learning model was trained to infer happy/sad emotional state using three publicly available emotional speech corpora in German and US English. We examined the models predictive ability to classify the presence of depression on Danish speaking healthy controls (N = 42), patients with first-episode major depressive disorder (MDD) (N = 40), and the subset of the same patients who entered remission (N = 25) based on recorded clinical interviews. The model was evaluated on raw, de-noised, and speaker-diarized data. ResultsThe model showed separation between healthy controls and depressed patients at the first visit, obtaining an AUC of 0.71. Further, speech from patients in remission was indistinguishable from that of the control group. Model predictions were stable throughout the interview, suggesting that 20-30 seconds of speech might be enough to accurately screen a patient. Background noise (but not speaker diarization) heavily impacted predictions. ConclusionA generalizable speech emotion recognition model can effectively reveal changes in speaker depressive states before and after remission in patients with MDD. Data collection settings and data cleaning are crucial when considering automated voice analysis for clinical purposes. Significant outcomes- Using a speech emotion recognition model trained on other languages, we predicted the presence of MDD with an AUC of 0.71. - The speech emotion recognition model could accurately detect changes in voice after patients achieved remission from MDD. - Preprocessing steps, particularly background noise removal, greatly influenced classification performance. Limitations- No data from non-remitters, meaning that changes to voice for that group could not be assessed. - It is unclear how well the model would generalize beyond Germanic languages. Data availability statementDue to the nature of the data (autobiographical interviews in a clinical population), the recordings of the participants cannot be shared publicly. The aggregated model predictions and code used to run the analyses is available at https://github.com/HLasse/SERDepressionDetection.

bioinformatics↗

Gut microbiome and its cofactors are linked tolipoprotein distribution profiles

Increasing evidence indicates that the gut microbiome (GM) plays an important role in the etiology of dyslipidemia. To date, however, no in-depth characterization of the associations between GM and its metabolic attributes with deep profiling of lipoproteins distributions (LPD) among healthy individuals has been conducted. To determine associations and contributions of GM composition and its cofactors with distribution profiles of lipoprotein subfractions, we studied blood plasma LPD, fecal short-chain fatty acids (SCFA) and GM of 262 healthy Danish subjects aged 19-89 years. Stratification of LPD segregated subjects into three clusters of profiles that reflected differences in the lipoprotein subclasses, corresponded well with limits of recommended levels of main lipoprotein fractions and were largely explained by host characteristics such as age and body mass index. Higher levels of HDL, particularly driven by large subfractions (HDL2a and HDL2b), were associated with a higher relative abundance of Ruminococcaceae and Christensenellaceae. Increasing levels of total cholesterol and LDL, which were primarily associated with large 1 and 2 subclasses, were positively associated with Lachnospiraceae and Coriobacteriaceae, and negatively with Bacteroidaceae and Bifidobacteriaceae. Metagenome sequencing showed a higher abundance of genes involved in the biosynthesis of multiple B-vitamins and SCFA metabolism among subjects with healthier LPD profiles. Metagenomic assembled genomes (MAGs) affiliated mainly to Eggerthellaceae and Clostridiales were identified as the contributors of these genes and whose relative abundance correlated positively with larger subfractions of HDL. The results of this study demonstrate that remarkable differences in composition and metabolic traits of the GM are associated with variations in LPD among healthy subjects. Findings from this study provide evidence for GM considerations in future research aiming to shade light on mechanisms of the GM - dyslipidemia axis.

systems biology↗

Targeting the MYC interaction network in B-cell lymphoma via histone deacetylase 6 inhibition

Overexpression of MYC is a genuine cancer driver in lymphomas and related to poor prognosis. However, therapeutic targeting of the transcription factor MYC remains challenging. Here, we show that inhibition of the histone deacetylase 6 (HDAC6) using the HDAC6 inhibitor Marbostat-100 (M-100) reduces oncogenic MYC levels and prevents lymphomagenesis in a mouse model of MYC-induced aggressive B-cell lymphoma. M-100 specifically alters protein-protein interactions by switching the acetylation state of HDAC6 substrates, such as tubulin. Tubulin facilitates nuclear import of MYC, and MYC-dependent B-cell lymphoma cells rely on continuous import of MYC due to its high turn-over. Acetylation of tubulin impairs this mechanism and enables proteasomal degradation of MYC. M-100 targets almost exclusively B-cell lymphoma cells with high levels of MYC whereas non-tumor cells are not affected. M-100 induces massive apoptosis in human and murine MYC-overexpressing B-cell lymphoma cells. We identified the heat-shock protein DNAJA3 as an interactor of tubulin in an acetylation-dependent manner and overexpression of DNAJA3 resulted in a pronounced degradation of MYC. We propose a mechanism by which DNAJA3 associates with hyperacetylated tubulin in the cytoplasm to control MYC turnover. Taken together, our data demonstrate a beneficial role of HDAC6 inhibition in MYC-dependent B-cell lymphoma.

cancer biology↗

RRP7A links primary microcephaly to radial glial cells and dysfunction of ribosomal biogenesis, neurogenesis and ciliary resorption

Introductory paragraphPrimary microcephaly (MCPH) is characterized by reduced brain size and intellectual disability1. The exact pathophysiological mechanism underlying MCPH remains to be elucidated, but dysfunction of neuronal progenitors in the developing neocortex plays a major role1. Using homozygosity mapping and whole exome sequencing, we identified a homozygous missense mutation (p.W155C) in Ribosomal RNA Processing 7 Homolog A, RRP7A, which segregated with MCPH in a consanguineous family with 10 affected individuals. RRP7A is expressed in neural stem cells/radial glial cells of the developing human forebrain, and targeted mutation of Rrp7a leads to defects in both neurogenesis and proliferation in a mouse stem cell model. RRP7A localizes to centrosomes, cilia and nucleoli, and patient-derived fibroblasts display defects in processing of ribosomal RNA, resorption of primary cilia and cell cycle progression. Finally, analysis of zebrafish embryos with loss-of-function mutation in rrp7a confirmed that RRP7A depletion causes reduced brain size, impaired neurogenesis and cell proliferation as well as defective ribosomal RNA processing. These findings provide novel insight into human brain development and MCPH.

neuroscience↗

An agent-based framework for improving wildlife disease surveillance: A case study of chronic wasting disease in Missouri white-tailed deer.

Epidemiological surveillance for important wildlife diseases often relies on samples obtained from hunter-harvested animals. A problem, however, is that although convenient and cost-effective, hunter-harvest samples are not representative of the population due to heterogeneities in disease distribution and biased sampling. We developed an agent-based modeling framework that i) simulates a deer population in a user-generated landscape, and ii) uses a snapshot of the in silico deer population to simulate disease prevalence and distribution, harvest effort and sampling as per user-specified parameters. This framework can incorporate real-world heterogeneities in disease distribution, hunter harvest and harvest-based sampling, and therefore can be useful in informing wildlife disease surveillance strategies, specifically to determine population-specific sample sizes necessary for prompt detection of disease. Application of this framework is illustrated using the example of chronic wasting disease (CWD) surveillance in Missouris white-tailed deer (Odocoileus virginianus) population. We show how confidence in detecting CWD is grossly overestimated under the unrealistic, but standard, assumptions that sampling effort and disease are randomly and independently distributed. We then provide adjusted sample size recommendations based on more realistic assumptions. These models can be readily adapted to other regions as well as other wildlife disease systems.

ecology↗

Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA

BackgroundBlood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion of cfDNA derived from tumor tissue in early-stage disease. A machine learning approach to discover signatures in cfDNA, potentially reflective of both tumor and non-tumor contributions, may represent a promising direction for the early detection of cancer.\n\nMethodsWhole-genome sequencing was performed on cfDNA extracted from plasma samples (N=546 colorectal cancer and 271 non-cancer controls). Reads aligning to protein-coding gene bodies were extracted, and read counts were normalized. cfDNA tumor fraction was estimated using IchorCNA. Machine learning models were trained using k-fold cross-validation and confounder-based cross-validation to assess generalization performance.\n\nResultsIn a colorectal cancer cohort heavily weighted towards early-stage cancer (80% stage I/II), we achieved a mean AUC of 0.92 (95% CI 0.91-0.93) with a mean sensitivity of 85% (95% CI 83-86%) at 85% specificity. Sensitivity generally increased with tumor stage and increasing tumor fraction. Stratification by age, sequencing batch, and institution demonstrated the impact of these confounders and provided a more accurate assessment of generalization performance.\n\nConclusionsA machine learning approach using cfDNA achieved high sensitivity and specificity in a large, predominantly early-stage, colorectal cancer cohort. The possibility of systematic technical and institution-specific biases warrants similar confounder analyses in other studies. Prospective validation of this machine learning method and evaluation of a multi-analyte approach are underway.

cancer biology↗

Critical Limb Ischemia Induces Remodeling of Skeletal Muscle Motor Unit and Myonuclear- and Mitochondrial-Domains

Critical limb ischemia, the most severe form of peripheral artery disease, leads to extensive damage and alterations in skeletal muscle homeostasis. Although recent developments towards revascularization therapies have been introduced, there has been limited research into treatments for ischemic myopathy. To elucidate the regenerative mechanism of the muscle stem cell and its niche components in response to ischemic insults, we explored interactions between the vasculature, motor neuron, muscle fiber, and the muscle stem cell. We first investigated changes in the neuromuscular junction and motor neuron innervation following a surgical hindlimb ischemia model of critical limb ischemia in mice. Along with previous findings that support remodeling of the neuromuscular junction, we report that ischemic injury also causes significant alterations to the myofiber through a muscle stem cell-mediated increase of myonuclei number per fiber, a concomitant decrease in myonuclear domain size, and an increase in relative mitochondrial content per myonucleus. These results indicate that as a regenerative response to critical limb ischemia, myofibers exhibit myonuclear expansion to allow enhanced transcriptional support and an increase in mitochondrial content for bioenergetic need of the energy-demanding tissue regeneration.

physiology↗

Quantitative and qualitative evaluation of the impact of the G2 enhancer, bead sizes and lysing tubes on the bacterial community composition during DNA extraction from recalcitrant soil core samples based on community sequencing and qPCR

Soil DNA extraction encounters numerous challenges that can affect both yield and purity of the recovered DNA. Clay particles lead to reduced DNA extraction efficiency, and PCR inhibitors from the soil matrix can negatively affect downstream analyses when applying DNA sequencing. Further, these effects impede molecular analysis of bacterial community compositions in lower biomass samples, as often observed in deeper soil layers. Many studies avoid these complications by using indirect DNA extraction with prior separation of the cells from the matrix, but such methods introduce other biases that influence the resulting microbial community composition.\n\nTo address these issues, a direct DNA extraction method was applied in combination with the use of a commercial product, the G2 DNA/RNA Enhancer(R), marketed as being capable of improving the amount of DNA recovered after the lysis step. The results showed that application of G2 increased DNA yields from the studied clayey soils from layers between 1.00 and 2.20 m below ground level.\n\nImportantly, the use of G2 did not introduce bias, as it did not result in any significant differences in the biodiversity of the bacterial community measured in terms of alpha and beta diversity and taxonomical composition.\n\nFinally, this study considered a set of customised lysing tubes for evaluating possible influences on the DNA yield. Tubes customization included different bead sizes and amounts, along with lysing tubes coming from two suppliers. Results showed that the lysing tubes with mixed beads allowed greater DNA recovery compared to the use of either 0.1 or 1.4 mm beads, irrespective of the tube supplier.\n\nThese outcomes may help to improve commercial products in DNA/RNA extraction kits, besides raising awareness about the optimal choice of additives, offering opportunities for acquiring a better understanding of topics such as vertical microbial characterisation and environmental DNA recovery in low biomass samples.

microbiology↗