Biology subjects

Ahmad, R.

Publications and source records attributed to Ahmad, R..

At least 19 recordsLinked to original sources

bioRxiv2026

The Wobble Uridine tRNA Writer MnmA Shapes Codon-Dependent Stress Response Systems

Escherichia coli uses wobble uridine (U34) modifications to tune codon decoding, but how individual tRNA writer enzymes shape gene expression remains unclear. Here, we identify MnmA, the U34 thiolation enzyme for tRNALys, tRNAGln, and tRNAGlu, as a central regulator linking codon-directed translation to regulon control and stress response. Loss of MnmA depleted s2U-dependent wobble modifications, preventing geranyl-(ges2U) and seleno-(se2U)-based modifications, causing growth defects, reduced catalase activity, and multi-level gene expression dysregulation. The {Delta}mnmA cells showed broad adaptive transcriptional reprogramming associated with RpoS- and OxyR-regulated pathways, which was accompanied by compromised protein output. Endogenous and tagged-protein analyses revealed specific impairment of transcriptional regulators, adaptive and detoxification proteins, including RpoS, OxyR, FliA, KatE, and KatG. Polysome profiling and polysome-associated RNA sequencing showed that MnmA deficiency globally reduces translational capacity and uncouples mRNA abundance from translational efficiency, which is exacerbated during oxidative stress. We developed genome-wide codon-usage mapping analytics to identify five codon-defined gene clusters, with specific clusters enriched for Lys, Gln, and Glu codons disproportionately affected by MnmA loss. Together, these findings support that wobble uridine thiolation and downstream modifications pair with corresponding codon architecture to coordinate the translation of regulon controllers and stress-response networks linked to bacterial fitness. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=159 HEIGHT=200 SRC="FIGDIR/small/745044v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1a4058borg.highwire.dtl.DTLVardef@167f4cdorg.highwire.dtl.DTLVardef@1f8c7a8org.highwire.dtl.DTLVardef@1fc0767_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2026

From culture to clarity in four hours: accelerating clinical management of bloodstream infections using metagenomics

BackgroundMetagenomic next-generation sequencing (mNGS) has the potential to transform clinical diagnostics for bloodstream infections (BSIs). However, its clinical utility is currently limited by several challenges, including the extraction of DNA from blood cultures. Our aim was to develop, evaluate, and optimize an in-house method for host depletion and bacterial DNA extraction from positive blood cultures to enable rapid mNGS-based pathogen detection and antimicrobial resistance profiling, informing clinical management of BSIs. Methods151 clinical blood cultures (115 positive and 36 negative) were processed for DNA extraction using an in-house-developed SEPSINN method for host depletion and bacterial DNA extraction. mNGS on the MinION was performed, and the results for pathogen identification and antimicrobial susceptibility predictions were compared with the routine clinical workflow. SEPSINN was also evaluated against a commercial DNA extraction method to assess its effectiveness in depleting host DNA and recovering bacterial DNA. ResultsThe SEPSINN method achieved up to 1000-fold depletion of host DNA and outperformed the commercial DNA extraction method. At the sample level, mNGS achieved 100% accuracy, specificity, and sensitivity, identifying at least one pathogen in all 115 positive blood cultures. At the pathogen level, mNGS showed 98% accuracy (120/123), specificity, and sensitivity. For antimicrobial susceptibility predictions, mNGS achieved an accuracy of 95% (1382/1451), a sensitivity of 88% (203/230), and a specificity of 97% (1179/1221). Moreover, the method also identified fungi, indicating a wider taxonomic range. mNGS resulted in an approximately 4-hour turnaround time for pathogen identification and resistance profiling. ConclusionsThe method can provide information on BSI clinical management within approximately 24 hours of receiving the sample, including the time required for culture positivity. This represents an important advancement in the clinical management of BSIs, with the potential to save lives and promote antibiotic stewardship.

microbiology↗

bioRxiv2026

Clinical Relevant Immunosuppressive Drugs Differentially Modulate Axonal Outgrowth from Human Stem Cell Derived Neurons

Neural stem cell (NSC) transplantation is a promising strategy for repairing the injured spinal cord, but transplanted cells typically require immunosuppressive therapy to prevent rejection--even for induced pluripotent stem cell (iPSC)-derived autologous grafts. However, the effects of immunosuppressive drugs on neurite outgrowth and axonal regeneration-- processes critical for neural circuit reconstruction--have not been fully characterized. In this study, we tested nine clinically relevant immunosuppressants on human iPSC-derived neurons and primary human spinal cord NSCs in vitro at concentrations approximating clinical exposure levels. The drug panel included FK-506 (tacrolimus), cyclosporine A (CsA), rapamycin, belatacept (Nulojix), etanercept (Enbrel), mycophenolate mofetil (CellCept), cyclophosphamide (Cytoxan), prednisone, and azathioprine (Imuran). Neurite outgrowth was quantified via automated high-content imaging. Multiple agents, including CsA, Imuran, Nulojix, and CellCept, induced significant reductions in neurite outgrowth in a cell type- and dose-dependent manner, with CsA producing the most robust and consistent inhibition across both cell lines. In contrast, FK-506 showed no significant effect on neurite extension at clinically relevant concentrations. Consistent with the in vitro results, human neural progenitor cell grafts in a rodent spinal cord injury model exhibited significantly reduced graft-derived axon extension in the host spinal cord when hosts were treated with CsA rather than FK-506. These findings demonstrate that immunosuppressant choice can profoundly influence neural graft integration and axonal regeneration. Our study underscores the importance of preclinical evaluation of immunosuppressive regimens and suggests that selecting agents such as FK-506 over CsA may improve outcomes in future stem cell-based therapeutic trials for spinal cord injury and related disorders of the central nervous system. HighlightsO_LICyclosporine A inhibits axon outgrowth in human neurons in vitro C_LIO_LIFK-506 preserves neurite extension across stem cell-derived neuron types C_LIO_LIAxon outgrowth is reduced in vivo with CsA but not FK-506 C_LIO_LIImmunosuppressant selection critically affects neural graft integration C_LIO_LIFK-506 may be preferable to CsA for SCI cell transplantation protocols C_LI

neuroscience↗

bioRxiv2026

An imaging framework for nuclei-based three-dimensional cell quantification in intact tissue using phase-contrast X-ray CT

Objective. Quantitative analysis of cellular morphology and spatial organisation within intact tissue remains challenging, particularly when three-dimensional information must be preserved. This study investigates whether laboratory propagation-based phase-contrast X-ray computed tomography (CT) can support nuclei-based quantitative analysis in unstained tissue while retaining the surrounding tissue architecture. Approach. We propose a nuclei-based quantitative imaging workflow that combines laboratory propagation-based phase-contrast X-ray CT with volumetric segmentation. Intact unstained liver tissue was imaged at cellular resolution, then nuclei were segmented throughout the reconstructed volume and quantitative metrics describing the nuclear morphology and spatial organisation were extracted. The resulting measurements were evaluated in two non-overlapping volumes of interest and compared with histological reference data using thickness-matched virtual CT slices. Main results. The proposed workflow enabled visualisation and segmentation of individual nuclei throughout intact unstained liver tissue. Comparable nuclear morphology and spatial organisation metrics were obtained from two non-overlapping volumes of interest, indicating stable segmentation performance within the analysed specimen. Comparison with H&E histology demonstrated broad agreement in nuclear morphology. Significance. This work demonstrates the feasibility of nuclei-based quantitative analysis using laboratory phase-contrast X-ray CT in intact unstained tissue. The approach provides volumetric cellular information while preserving tissue architecture and may complement conventional histological assessment in applications requiring three- dimensional analysis. These findings highlight the potential of laboratory phase-contrast CT for quantitative tissue characterisation and spatial cellular analysis

bioengineering↗

bioRxiv2026

Developmental transcriptomic analysis of cultured primary mouse cortical neurons reveals sex-specific expression of neuropeptides

Primary neuronal cultures derived from mouse tissue serve as an essential model for investigating neuronal development and function. Despite this, comprehensive developmental and sex-specific transcriptomic profiles in primary neurons have not been defined. Here, we performed multiplexed RNA-sequencing of neurons derived from male and female cortices across time. We validated this approach by assessing established neuronal maturation genes and we identified highly stable genes to serve as controls across development. Next, using linear modeling and temporal regression, we defined developmentally regulated transcripts, longitudinal expression dynamics, and gene signatures associated with transition states throughout development. Unexpectedly, this also revealed sex-specific effects on autosomal genes that emerge only after neuronal maturation even in the absence of in vivo cues. Most notably, neuropeptide genes Cortistatin and Neurokinin A are more highly expressed in female neurons. Furthermore, exposure to these neuropeptides elicited distinct transcriptional responses in male-versus female-derived cultures. These findings provide a valuable resource and reveal sex-specific autosomal transcriptional signatures that emerge in neurons maintained ex vivo. HighlightsO_LIMultiplexed RNA-sequencing of primary cultured neurons across neuronal maturation provides a new resource for the field. C_LIO_LIGene signatures associated with transition states are identified through linear modeling. C_LIO_LISex-specific regulation of autosomal genes encoding neuropeptides emerge even in the absence of in vivo cues. C_LIO_LIExposure to neuropeptides elicit distinct transcriptional responses in male and female primary neurons. C_LI

neuroscience↗

bioRxiv2026

Rapid clinical metagenomics enables early tailored therapy in complicated urinary tract infections and strengthens antimicrobial stewardship

Rapid and accurate diagnosis of UTIs remains difficult because culture-based methods are slow and less sensitive. This study evaluates URINN, a metagenomic workflow that detects uropathogens, antibiotic resistance genes, and virulence factors directly from patient urine samples. The optimized protocol was tested on a combined set of 349 clinical urine samples. URINN demonstrated 99% accuracy across all samples and 97% sensitivity for identifying 294 pathogens, including both bacteria and fungi. It predicted antibiotic susceptibility with 91% accuracy across 2099 antibiotics. The method detected pathogens at concentrations as low as 9.3 x 103 CFU/mL and provided results within approximately four hours. Flow cytometry and DNA yield analyses helped establish thresholds to differentiate culture-positive from culture-negative samples, with genome coverage linked to the accuracy of susceptibility predictions for certain species. Virulence profiling revealed that adherence and nutritional factors are crucial for colonization and persistence. Leukocyte counts were comparable between genders, but bacterial loads were higher in females. The catheterized group had significantly higher leukocyte counts, and their urine showed increased cephalosporin resistance. This approach could enhance clinical decision-making, support personalized treatment, and improve the management of complicated UTIs, thereby contributing to better UTI care and antibiotic stewardship.

genomics↗

bioRxiv2026

Exposure to a low dose mixture of endocrine disrupting chemicals alters the brain transcriptome and animal behavior

Exposures to pervasive chemical toxicants such as endocrine disrupting chemicals (EDCs) are associated with adverse neurological and neurodevelopmental deficits. Although EDCs are widespread as sparse mixtures in the environment, most research has focused on single chemicals at high concentrations. Here, we studied the effects of ldEDC: a low-dose mixture of widely prevalent toxicants at doses representative of normal human exposure levels. Primary cultured mouse neurons treated with ldEDC exhibited altered gene expression compared to vehicle controls in genes critical for neuron activity, indicating low doses EDCs can affect neuronal function directly. We next tested persistent exposure through the maternal diet to define perinatal effects on offspring. Exposed offspring exhibited differences in development, tactile sensitivity, and sex-specific changes in motor behavior. Cortical single-nuclei sequencing identified broad transcriptomic changes, particularly in distinct cortical layer subpopulations, excitatory neurons, and astrocytes. Cell-cell signaling between neurons and non-neuronal populations were altered in exposed mice, specifically in pathways associated with cellular adhesion. Transcriptomic differences were also sex-specific. Together, these in vitro and in vivo findings reveal molecular and phenotypic consequences of EDC exposure at a mixture of doses well below commonly studied levels and highlights common functional pathways of susceptibility.

neuroscience↗

bioRxiv2025

K-MARVEL: K-Mer based Antimicrobial Resistance Virtual Exploration Lab

The rapid global spread of antimicrobial resistance (AMR) necessitates a new generation of computational tools for its surveillance. While next-generation sequencing offers unprecedented insight into the resistome, current methods face a trade-off: assembly-based approaches are computationally expensive and struggle with complex metagenomes, whereas direct-mapping of long reads is hampered by high error rates that obscure critical resistance-conferring mutations. Here, we present K-MARVEL (K-Mer based Antimicrobial Resistance Virtual Exploration Lab), a novel, open-source method to capture ARGs and resistance-conferring mutations from short and long-read sequencing datasets. It operates in protein k-mer space, providing inherent tolerance to nucleotide-level sequencing errors. On a comprehensive benchmark of 61 long and 49 short-read diverse datasets, K-MARVEL demonstrated superior accuracy, achieving F1-scores of 0.9783 and 0.9754 for short and long-read datasets, respectively. Its implementation in Rust enables high speed through parallelization while guaranteeing memory safety. Computationally, it demonstrated superior performance to conventional assembly-based methods, achieving an average speed up of 7x on short-read datasets and 5x on long-read datasets. In terms of memory footprint, it outperformed the assembly-based approaches for short-read datasets, but its memory footprint was comparable for long-read datasets. Notably, K-MARVEL accurately reconstructs functional genes from genomically fragmented evidence, providing a more comprehensive resistome assessment. In conclusion, K-MARVEL provides a scalable, flexible and memory-efficient solution for AMR surveillance. Its unique capabilities for handling noisy long-read data and complex genomic scenarios make it a powerful tool for researchers and public health scientists. K-MARVEL is open-source and freely available at https://bitbucket.org/amr-avenger/k-marvel under the GPL version 3 license.

bioinformatics↗

bioRxiv2025

Mango: Unearthing Patterns in Large-Scale Biological Data Through Interactive Correlation Analysis

Integrating different types of biological data is often challenging due to the presence of both numerical and categorical data. This complexity makes it harder to evaluate causal biological effects, especially when confounders like population structure, sampling methods, or multi-omics integration can lead to incorrect conclusions. We introduce Mango, an interactive correlation browser designed for visually exploring any tabular data type, using a novel algorithm to correlate numerical and categorical data, regardless of their distribution, called Median-Ranked Label Encoding. Our results on genomic and transcriptomic datasets demonstrate that these correlations can effectively distinguish between biases and causal relationships in large-scale data.

bioinformatics↗

bioRxiv2025

Comparative Machine Learning Analysis of Saliva and Plaque Microbiomes in Children with Type 1 Diabetes

BackgroundType 1 diabetes (T1D) is associated with microbial dysbiosis. While most research has focused on the gut microbiome, limited data address the role of the oral microbiome in T1D. The oral and gut microbiomes overlap substantially, and the oral cavity may influence the gut microbial composition. Saliva and dental plaque represent two distinct oral niches with unique microbial communities, but it remains unclear which better reflects systemic disease states such as T1D. This study compared the performance of salivary and plaque microbiomes in classifying pediatric T1D status. MethodsPaired saliva and plaque samples were collected from 46 children (23 with T1D and 23 healthy controls). Microbial DNA was extracted and sequenced to target the 16S rRNA gene. The data were processed via QIIME 2 for taxonomic classification and centered log-ratio transformation. Alpha diversity, microbial abundance, and clustering analyses were performed to compare the oral microbiome between the T1D and control groups. Random forest classifiers were used to evaluate and compare the predictive accuracy of saliva- and plaque-based models, both with and without clinical metadata. ResultsSaliva samples presented lower alpha diversity than plaque samples did but presented significantly greater bacterial loads and total microbial abundances. Saliva-based models outperformed plaque-based models, achieving a classification accuracy of 94.2% with or without clinical metadata, compared with 73.3% accuracy for plaque-based models. ROC curve analysis further supported this difference, with saliva models reaching an AUC of approximately 0.94 versus 0.75 for plaque, indicating superior discriminative performance. UMAP clustering revealed more distinct separation of the T1D and control groups in terms of the salivary profiles than in the plaque profiles. Feature importance analysis revealed both unique and shared taxa predictive of T1D in each niche. The incorporation of clinical and demographic metadata did not enhance model performance, underscoring the robustness and predictive strength of microbiome data alone. ConclusionThe salivary microbiome is a more effective biospecimen than dental plaque for detecting T1D-associated microbial profiles in children. It offers superior classification accuracy and greater sensitivity in distinguishing T1D status, supporting salivas potential as a noninvasive, scalable medium for future microbiome-based monitoring.

microbiology↗

bioRxiv2025

Optimizing Sample Preparation for Direct Nanopore Sequencing to Enable Rapid Pathogen and Antimicrobial Resistance Profiling in Bovine Mastitis

Long-read metagenomic sequencing allows for the rapid, culture-independent, and accurate identification of causative pathogens and antimicrobial resistance (AMR) profiles, supporting precise antibiotic use and reducing the spread of resistance. However, its application to mastitis milk is challenging due to the complex milk matrix, low bacterial count, and high somatic cell content. This study primarily aimed to further optimize our previously developed direct sequencing protocol for milk samples from mastitis cases. Additional optimizations included combining centrifugation, gradient centrifugation, and fat fraction treatment with Tween 20 and citric acid. Subsequently, four DNA extraction kits (Blood and Tissue, Molysis Complete5, HostZero, and SPINeasy Host depletion) were evaluated for their ability to remove host DNA and enrich bacterial DNA for long-read sequencing with Oxford Nanopore technologies. qPCR was used to quantify bacterial and bovine DNA, allowing comparison of host depletion efficiency among the kits. Our results show that simple centrifugation effectively concentrates bacterial cells, removing the need for chemical treatments. The HostZero kit consistently produced higher DNA yields, better DNA integrity, and more effective host DNA depletion. Using nanopore sequencing, both Gram-positive and Gram-negative mastitis pathogens, along with their AMR genes, were successfully detected. Overall, this study underscores the importance of an effective DNA extraction method for the direct sequencing of mastitis milk samples. Additionally, our findings support the potential of direct metagenomic sequencing as a rapid, culture-free approach for identifying mastitis pathogens and their resistance profiles.

microbiology↗

bioRxiv2025

Connections in the Dark: Social-Ecological Networks as a Promising Tool for Bat Conservation and One Health

Bats provide vital ecosystem services, including pest suppression and crop pollination. However, the increasing proximity of bats and humans is a growing conservation and public health concern with negative consequences for both sides. Mitigating these consequences requires integrative approaches like network science and the emerging field of social-ecological networks (SENs), which offer powerful tools to map and analyse complex social and ecological dynamics. Here, we synthesize how network approaches have been applied to bat research and conservation. Specifically, we: (i) assess the use of both ecological and social network analyses to study bats; (ii) identify network tools well-suited for SEN-based bat research; (iii) present a case study illustrating how SEN applications in bat research can inform conservation and One Health efforts; and, lastly, (iv) discuss key challenges and opportunities in using SENs to investigate the human-bat interface. Our review unveils a rise in network-based bat research from 2006 to 2020, followed by a post-pandemic decline. Nevertheless, across the 127 studies mapped by our review, only one applied an SEN lens. Finally, we suggest how applying some underexplored SEN tools to bat research could lead to novel perspectives, aiming to promote integrated strategies for the coexistence of bats and humans.

ecology↗

bioRxiv2025

Development and optimization of the host DNA depletion in blood cultures using a saponin and SAN nucleases-based method

Bloodstream infections and sepsis are major health issues causing millions of deaths annually. Early and accurate diagnosis of sepsis is crucial for reducing mortality and combating antimicrobial resistance. However, current diagnostic methods are slow and time-consuming. Nanopore sequencing has the potential to serve as a rapid diagnostic method for sepsis. However, extracting bacterial DNA from blood samples is challenging due to the high content of host DNA. This study aimed to develop and optimize a method using saponin and SAN nucleases for effective host DNA depletion in blood cultures. Different concentrations of saponin, HL-SAN, and M-SAN nucleases, combined with various salt conditions (NaCl and MgCl2), were tested for their ability to deplete host DNA in blood cultures spiked with E. coli and S. aureus. The impact of different bead beating durations on DNA fragment sizes was also examined. The efficiency of host DNA depletion and bacterial DNA extraction was assessed using quantitative PCR (qPCR) and nanopore sequencing. Results indicated that 4% of saponin effectively lysed host cells, releasing DNA while preserving bacterial cells. The host DNA is then efficiently depleted using 250 units (10 L) of HL-SAN and M-SAN nucleases. Although SAN in combination with higher salt concentrations (2.5 M NaCl and 50 mM MgCl2) showed somewhat better host DNA removal, the difference was not statistically significant. Reducing bead beating time to 6 minutes improved the recovery of longer DNA fragments compared to 10 minutes. These results demonstrate an effective method for host DNA depletion using saponin and SAN nucleases, which is compatible with downstream processes, such as nanopore sequencing and qPCR.

microbiology↗

bioRxiv2025

Low-Cost In-House Re-formulated Brain Heart Infusion Medium for Effective Planktonic Growth and Early Detection of Bloodstream Bacterial Pathogens

Sepsis, a clinically defined life-threatening condition, is a global contributor to high morbidity and mortality rates in humans. It is caused by systemic bloodstream bacterial infections, primarily involving aerobic pathogens such as Escherichia coli, Staphylococcus aureus, and Klebsiella pneumoniae. Rapid and accurate identification of these pathogens is a high-demand task, as prolonged diagnosis may increase the mortality rate among sepsis patients. Worldwide, commercial blood culture systems, such as BD BACTEC PLUS Aerobic/F /F culture bottles (used in this study), are routinely used to monitor bloodstream infections. However, due to high costs ($10.00-$15.00/bottle), limited availability of culture media (especially in low- and middle-income countries, and war zones), and a lack of customization for antibiotic susceptibility assay and epidemiology research, there is a need for secondary alternatives to facilitate the growth and identification of bloodborne pathogens. Therefore, we developed a low-cost ($4-$5/bottle) in-house culture medium with a newly improved formulation of Brain Heart Infusion media that enhances bacterial growth from spiked human blood tested on a panel of bacteria (Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterococcus faecalis). The growth dynamics of these microbes in in-house formulated BHI-Blood+ culture media coincide with those in BACTEC Plus Aerobic/F culture vials, which primarily suggests the compatibility of bloodborne pathogens with this media and can be flagged positive <8h based on cellular growth rate. Additionally, conventional qPCR-based early detection (< 24h) and validation with the Oxford Nanopore MinION NGS platform highlight the value of this in-house culture media as an alternative to commercial culture media in terms of low-cost availability.

microbiology↗

bioRxiv2025

Autism spectrum disorder risk genes have convergent effects on transcription and neuronal firing patterns in primary neurons

Autism spectrum disorder (ASD) is a highly heterogenous neurodevelopmental disorder with numerous genetic risk factors. Notably, a disproportionate number of risk genes encode transcription regulators including transcription factors and proteins that regulate chromatin. Here, we teste the function of nine such ASD-linked transcription regulators by depleting them in primary cultured neurons. We then define the resulting gene expression disruptions using RNA-sequencing and test effects on neuronal firing using multielectrode array recordings. We identify shared gene expression signatures across many ASD risk genes that converge on disruption of critical synaptic genes. Fitting with this, we detect robust disruptions to neuronal firing throughout neuronal maturation. Together, these findings provide evidence that loss of multiple ASD-linked transcriptional regulators disrupts transcription of synaptic genes and has convergent effects on neuronal firing that may contribute to enhanced ASD risk.

neuroscience↗

bioRxiv2025

Eicosapentaenoic Acid (EPA) Alleviates LPS-Induced Oxidative Stress via the PPARa-NF-kB Axis

Metabolic-endotoxemia, characterized by the translocation of lipopolysaccharide (LPS) from Gram-negative bacteria into the bloodstream, is a key contributor to chronic low-grade inflammation associated with obesity and type 2 diabetes. This condition exacerbates metabolic disruptions by activating Toll-like receptor 4 (TLR4) on macrophages, leading to the release of pro-inflammatory cytokines and subsequent insulin resistance. Eicosapentaenoic acid (EPA/C20:5), an omega-3 polyunsaturated fatty acid, has demonstrated anti-inflammatory and antioxidative properties, but its precise mechanisms of action in mitigating LPS-induced stress remain unclear. This study investigates the pathways through which EPA/C20:5 alleviates LPS-induced oxidative stress and inflammation in macrophages. EPA pretreatment significantly reduced LPS-induced inflammatory responses, decreasing IL-1{beta} and IL-6 expression and IL-1{beta} secretion, and lowering the percentage of HLA-DR macrophages. EPA also attenuated ER stress, evidenced by reduced expression of ATF4, DDIT3, HSPA5/GRP78, BIP, and CHOP at both gene and protein levels. Oxidative stress was mitigated, as shown by decreased HIF1 expression, reduced ROS levels, and preservation of mitochondrial membrane potential. Importantly, EPA increased the expression of PPAR and FABP5 while inhibiting NF-{kappa}B activation independently of the TLR4-IRF5 pathway. The protective effects of EPA were abolished by PPAR inhibition with GW9662, indicating that EPAs action is PPAR-dependent. This study highlights the modulatory role of EPA in alleviating LPS-induced oxidative stress and inflammation in macrophages through activation of the FABP5/PPAR/NF-{kappa}B axis, independently of TLR4-IRF5 signaling. These findings reveal a novel mechanism for EPAs anti-inflammatory effects and suggest that targeting the FABP5/PPAR pathway may offer therapeutic potential for treating metabolic disorders associated with chronic inflammation.

molecular biology↗

bioRxiv2024

Real-time Taxonomic Characterization of Long-read Mixed-species Sequencing Samples in Sorted Motif Distance Space: Voyager

Recent advances in long-read sequencing technology enable its use in potentially life-saving applications for rapid clinical diagnostics and epidemiological monitoring. To take advantage of these enabling characteristics, we present Voyager, a novel algorithm that complements real-time sequencing by rapidly and efficiently mapping long sequencing reads with insertion- and deletion errors to a large set of reference genomes. The concept of Sorted Motif Distance Space (SMDS), i.e., distances between exact matches of short motifs sorted by rank, represents sequences and sequence complementarity in a highly compressed form and is thus computationally efficient while enabling strain-level discrimination. In addition, Voyager applies a deconvolution algorithm rather than reducing taxonomic resolution if sequences of closely related organisms cannot be discerned by SMDS alone. Using relevant real-world data, we evaluated Voyager against the current best taxonomic classification methods (Kraken 2 and Centrifuge). Voyager was on average more than twice as fast as the current fastest method and obtained on average over 40% higher species level accuracy while maintaining lower memory usage than both other methods.

bioinformatics↗

bioRxiv2024

Detection of pathogens and antimicrobial resistant genes from urine within 5 hours using Nanopore sequencing

PurposeUrinary Tract Infection (UTI) is a prevalent global health concern accounting for 1-3% of primary healthcare visits. The current methods for UTI diagnosis have a high turnaround time of 3-5 days for pathogen identification and susceptibility testing. This work is a proof-of-concept study aimed at determining the detection limit by establishing a culture and amplification-free DNA extraction methodology from spiked urine samples followed by real-time Nanopore sequencing and data analysis. MethodsThis study first establishes an optical density culture-based method for spiking healthy urine samples with the six most prevalent uropathogens. Pathogens were spiked at two clinically significant concentrations of 103 and 105 CFU/ml. Three commercial DNA extraction kits were investigated based on the quantity of isolated DNA, average processing time, elution volume and the average cost incurred per extraction. The outperforming kit was used for direct DNA extraction and subsequent sequencing on MinION and Flongle flowcells. ResultsThe Blood and Tissue kit outperformed the other kits. All pathogens were identified at a concentration of 105 CFU/ml within ten minutes, and the corresponding AMR genes were detected within three hours of the sequencing start. The overall turnaround time including the DNA extraction and sequencing steps was five hours. Moreover, we also demonstrate that the identification of some pathogens and antibiotic-resistance genes was possible at a spike concentration of 103 CFU/mL. ConclusionThis study shows great promise toward reducing the time required for making an informed antibiotic administration from approximately 48 hours to five hours thereby reducing the number of empirical doses and saving lives.

microbiology↗