Biology subjects

Mohammadi, S.

Publications and source records attributed to Mohammadi, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Amino Sugar Metabolism with AgaSY Coordinates Carbon Catabolism, Fimbrial Regulation, and Pathogenesis in Uropathogenic E. coli

Uropathogenic Escherichia coli (UPEC) exploit alternative carbon sources in order to adapt to the nutrient-limited urinary tract. While glucose is often scarce in healthy human urine, UPEC express a variety of sugar transport and catabolic systems that promote fitness during infection. In this study, we identify the agaSY genes in UPEC strain CFT073 as essential for the catabolism of the amino sugars N-acetyl-galactosamine (GalNAc or Aga) and galactosamine (GalN or Gam) and for the efficient use of additional amino sugars and carbon sources. Deletion of agaSY not only abolished Aga utilization but also impaired catabolism of multiple carbon sources including amino acids and sugars tested using phenotypic arrays. The {Delta}agaSY mutant exhibited significantly reduced type 1 fimbriae production, reduced biofilm formation, and increased motility, suggesting a link between amino sugar metabolism and the regulation of bacterial surface structures. Loss of agaSY did not affect growth and adherence to bladder cells and increased expression of genes encoding F9 fimbriae. Furthermore, the {Delta}agaSY mutant was significantly attenuated for bladder and kidney colonization in a murine urinary tract infection model, while complementation restored urinary tract colonization. The results indicate that a combination of deficiencies in nutrient acquisition, altered carbon metabolism, and regulation of virulence-associated factors contributes to reduced urinary tract colonization. Our findings highlight the interplay between metabolic flexibility and virulence regulation, as well as the central role that amino sugar metabolism plays in UPEC pathogenesis.

microbiology↗

bioRxiv2026

Cross-Serogroup Analysis of Representative Top-Seven Shiga toxin-producing Escherichia coli Plasmids Reveals Lineage-Specific Patterns

Plasmids play a significant role in shaping the pathogenic potential of Shiga toxin-producing Escherichia coli (STEC) by encoding virulence and adaptive genes that complement chromosomal determinants. While plasmid-encoded factors such as ehxA, espP, katP, and toxB are known to enhance intestinal colonization and host interaction, the diversity and evolutionary patterns of STEC plasmids remain insufficiently characterized. Most previous studies have focused on single serogroups, particularly O157, leaving cross-serogroup comparisons largely unexplored. To address this gap, we conducted an in-depth investigation of 109 complete plasmid sequences (1.5-187 kb) from the "Top Seven" STEC serogroups (O26, O45, O103, O111, O121, O145, and O157), retrieved from NCBI, to examine their structural organization, virulence composition, resistance patterns, mobility potential, and evolutionary dynamics. Our analysis revealed the dominance of F-type plasmids carrying IncFIB and IncFII replicons across serogroups, along with lineage-specific associations with major virulence genes. By examining the enterohemolysin operon across ehxA-positive plasmids, we identified a highly conserved structural framework maintained across 92.5% of analyzed sequences, with minimal variation. We further characterized antimicrobial resistance gene distribution, finding that only 11% of plasmids (12/109) carried such genes, of which 92% were multidrug-resistant. Analysis of mobility features revealed that predicted conjugative potential and MOBF-type relaxases varied considerably among serogroups. The 32 plasmids without virulence or resistance cargo carried at most colicin determinants, yet all received a predicted mobility class, with conjugative machinery confined to plasmids above 37 kb. At the plasmid level, serogroups O26/O103 are closely related and carry relatively high-risk virulence profiles, while the O121/O145 group exhibits moderate virulence gene inventories. The O45/O111 group is further distinguished by its transfer features, while O157 strains form a distinct clade with the broadest array of plasmid-encoded high-risk virulence genes.

microbiology↗

bioRxiv2026

Diffusion tensor imaging of whole human brains during long-term formaldehyde fixation: Temporal evolution of diffusion parameters, post-mortem conditions, and dependence on tissue structure

Purpose: Post-mortem Diffusion Magnetic Resonance Imaging (dMRI) findings on fixation-related changes in diffusion tensor imaging (DTI) parameters remain inconsistent, partly due to lower diffusion weighting and sparse early-fixation sampling. This study investigated how post-mortem tissue condition, fixation progression, and diffusion weighting shape DTI parameters in whole human brains, including whether an ex-vivo-adjusted protocol also suits in-situ and early fixation measurements. Methods: Six neurologically healthy whole human brains (post-mortem interval (PMI) 12 - 24 h) were scanned across tissue conditions, including an in-vivo reference cohort. Five brains were scanned longitudinally through immersion fixation (0 - 150 days), yielding 175 datasets with dense early sampling. Diffusion measurements at b-values 1000 - 4000 s/mm2 assessed the influence of diffusion weighting on DTI parameters. Analyses covered multiple white- and gray-matter regions and within white matter stratification by fiber orientation dispersion ({kappa}). Results: The largest mean diffusivity (MD) shift occurred between in-vivo and in-situ, whereas fractional anisotropy (FA) changed most strongly during early fixation. During immersion fixation, MD showed reproducible monoexponential saturation, while FA was heterogeneous across brains. PMI, {kappa}, and regional anatomy explained substantial FA heterogeneity across specimens. Qualitatively, the fixationrelated changes matched across diffusion weightings, but precision across specimens was highest at b-value 4000 s/mm2. Conclusion: During fixation, MD is a robust temporal marker, whereas FA requires microstructureaware interpretation. Diffusion weighting modulates how clearly fixation effects can be resolved, but the same qualitative fixation dynamics remained detectable at in-vivo-like weighting with reduced precision.

neuroscience↗

bioRxiv2026

3D Histology Validates 2D Histology for Axon Radius Distributions and Conduction Velocities

Axons are the brains wiring, organized into bundles that connect nearby and distant regions. Axon caliber determines signal conduction velocity and varies both within and across bundles, reflecting the brains diverse functional demands. Much of what we know about this organization derives from 2D histology, assuming cylindrical axons whose calibers are described by their radius. Yet, recent 3D histology reveals that the radius varies along an individual axon--with implications for both characterizing axon caliber and potentially conduction velocity predictions. We show in 450,000 3D rat axon reconstructions that--despite this individual variation--axon bundles possess stable radius distributions at the ensemble level, which 2D cross-sections faithfully represent. This representativeness extends to conduction velocity predictions, as along-axon variation has only modest impact. In particular, large axons exhibit especially stable conduction, emphasizing their key role in time-critical signaling. With 2D sampling validated, we leverage 46 million human corpus callosum axons from 2D histology to determine sample size requirements across neuroscience applications. Our findings reinforce decades of 2D histology-based research on axon organization and its functional implications, while guiding future study design.

neuroscience↗

bioRxiv2026

Foundation Models Improve Perturbation Response Prediction

Predicting cellular responses to genetic or chemical perturbations has been a long-standing goal in biology. Recent applications of foundation models to this task have yielded contradictory results regarding their superiority over simple baselines. We conducted an extensive analysis of over 600 different models across various prediction tasks and evaluation metrics, demonstrating that while some foundation models fail to outperform simple baselines, others significantly improve predictions for both genetic and chemical perturbations. Furthermore, we developed and evaluated methods for integrating multiple foundation models for perturbation prediction. Our results show that with sufficient data, these models approach fundamental performance limits, confirming that foundation models can improve cellular response simulations. Code and Data: https://github.com/genbio-ai/foundation-models-perturbation

bioinformatics↗

bioRxiv2026

Longitudinal whole-human-brain quantitative MRI study on autolysis, fixation, rehydration, and shrinkage effects

Postmortem MRI links in vivo MRI contrast to microstructure measured with ex vivo histology, yet fixation systematically alters relevant physical MRI parameters. We quantified these effects by longitudinally characterizing multi-parametric mapping (MPM) measures - longitudinal (R1) and effective transverse (R2*) relaxation rates, normalized proton density proxy (NA), and magnetization transfer saturation (MTsat) - and tissue-volume change in five whole human brains scanned unfixed ex vivo in situ, during formaldehyde immersion fixation, and, when available, after transfer to phosphate buffered saline solution. We included an independent in vivo cohort of 25 younger healthy participants to provide a qualitative in vivo reference. The largest changes were found for R1 during fixation relative to in situ values (up to 351% in dGM), followed by R2* (up to 60% in WM). NA was largely unchanged during fixation. Although MTsat decreased by up to 25% in gray matter from in vivo to in situ, it largely preserved tissue contrast during fixation and PBS immersion, making it an ideal candidate for longitudinal registration across tissue conditions. Phenomenological models characterized fixation-induced parameter changes and relative tissue-volume change. R1 and fixation-associated volume loss evolved under broadly similar timescales, consistent with a contribution from fixation-related water loss or redistribution. This densely sampled dataset and analyses provide a resource for linking in vivo MRI to postmortem fixed-tissue MRI and ex vivo histology under a standardized immersion-fixation protocol.

neuroscience↗

bioRxiv2025

Historical Contingency Shapes Toxin Resistance in a Specialist Avian Predator

Adaptations to toxic diets can cascade through ecosystems, altering physiology, species interactions, and trophic dynamics. To uncover the molecular basis of toxin resistance in the black-headed grosbeak (Pheucticus melanocephalus), a specialist predator of cardiotonic steroid-defended monarch butterflies (Danaus plexippus), we investigated the evolution of target-site insensitivity in the toxins molecular target - the Na,K-ATPase. Functional assays of engineered Na,K-ATPases revealed that resistance in grosbeaks arises from a non-additive interaction between a substitution at position 111 (Q111E) and up to six nearby amino acid changes in the first extracellular loop of the protein. Using resurrected ancestral proteins, we show that the earliest of these six substitutions to evolve (V113L) altered the functional effects of Q111E, such that Q111E alone became maladaptive. Only after the accumulation of additional permissive substitutions could Q111E confer resistance, highlighting how intramolecular epistatic interactions and historical contingency constrained the evolutionary path to adaptation. Our phylogenetic analysis of Na,K-ATPase sequences from 360 birds further revealed that several of the specific grosbeak substitutions--particularly at sites 112, 114, and 116--show strong signatures of co-evolution with changes at site 111 across the avian tree, supporting the hypothesis that resistance evolves through repeated, interacting changes. Together, these results reveal the molecular mechanisms of convergent evolution of toxin resistance and demonstrate how genetic background can shape evolutionary outcomes across trophic levels.

evolutionary biology↗

bioRxiv2025

Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction

The decreasing cost of single-cell RNA sequencing (scRNA-seq) has enabled the collection of massive scRNA-seq datasets, which are now being used to train transformer-based cell foundation models (FMs). One of the most promising applications of these FMs is perturbation response modeling. This task aims to forecast how cells will respond to drugs or genetic interventions. Accurate perturbation response models could drastically accelerate drug discovery by reducing the space of interventions that need to be tested in the wet lab. However, recent studies have shown that FM-based models often struggle to outperform simpler baselines for perturbation response prediction. A key obstacle is the lack of understanding of the components driving performance in FM-based perturbation response models. In this work, we conduct the first systematic pan-modal study of perturbation embeddings, with an emphasis on those derived from biological FMs. We benchmark their predictive accuracy, analyze patterns in their predictions, and identify the most successful representation learning strategies. Our findings offer insights into what FMs are learning and provide practical guidance for improving perturbation response modeling.

bioinformatics↗

bioRxiv2025

Enhanced mRNA delivery using ultrasound-delivered click reactive anchors

Therapeutic nucleic acid delivery has many potential applications, but it remains challenging to target extrahepatic tissues in a flexible and image-guided manner. To address this issue, we report a bioorthogonal pre-targeting strategy that uses focused ultrasound to promote the delivery of mRNA-loaded lipid nanoparticles (mRNA-LNP). We synthesized amphiphilic click reactive anchors (ACRAs) consisting of a phospholipid PEG-conjugate functionalized with transcyclooctene (TCO) or its companion reactive partner methyltetrazine (mTz), yielding ACRA-TCO and ACRA-mTz. ACRA derivatives were screened for cellular activity, yielding functionalized DOPE-PEG (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine-N- (polyethylene glycol)) derivatives outperforming those containing saturated lipid or branched PEG. Nanobubbles encapsulating ultrasound-responsive gas precursor delivered ACRA-TCO to targeted cells and tissues using focused ultrasound, and this pre-targeting promoted the subsequent delivery of mRNA- LNP functionalized with companion ACRA-mTz. In cell cultures and in mice, ultrasound pre-targeting enhanced the accumulation of mTz-functionalized small molecule and nanoparticle compounds by 75% and 3.6-fold, respectively, and increased gene expression using mRNA-LNP in vivo. Taken together, this report presents a modular, ultrasound-enabled strategy for enhancing nucleic acid delivery in targeted tissues.

bioengineering↗

bioRxiv2024

Human short association fibers are thinner and less myelinated than long fibers

The size and complexity of the human brain requires optimally sized and myelinated fibers. White matter fibers facilitate fast communication between distant areas, but also connect adjacent cortical regions via short association fibers. The fundamental questions of i) how thick these fibers are and ii) how strongly they are myelinated, however, remain unanswered. We present a comprehensive analysis of [~]400,000 fibers of human white matter regions with long (corpus callosum) and short fibers (superficial white matter). We demonstrate a substantially smaller fiber diameter and lower myelination in superficial white matter than in the corpus callosum. Surprisingly, we do not find a difference in the ratio between axon diameter and myelin thickness (g-ratio), which is close to the theoretically optimal value of [~]0.6 in both areas. For the first time, to our knowledge, we shed light on a fundamental principle of brain organization that will be essential to understand the human brain.

neuroscience↗

bioRxiv2024

Evaluating the efficacy of protein quantification methods on membrane proteins

Protein quantification is an important tool for a wide range of biological applications. The most common broadscale methods include the Lowry, bicinchoninic acid (BCA), and Coomassie Bradford assays. Despite their wide applicability, the mechanisms of action imply that these methods may not be ideal for large transmembrane proteins due to the proteins integration in the plasma membrane. Here, we investigate this problem by assessing the efficacy and applicability of these three common protein quantification methods on a candidate transmembrane protein - the Na,K-ATPase (NKA). We compared these methods to an ELISA, which we newly developed and describe here for the quantification of NKA. The use of a relative standard curve allows this ELISA to be easily adapted to other proteins and across the animal kingdom. Our results revealed that the three conventional methods significantly underestimate the concentration of NKA compared to the ELISA. Further, by applying the protein concentrations determined by the different methods to in vitro assays, we found that variation in the resulting data was consistently low when the assay reactions were prepared based on concentrations determined from the ELISA. Thus, when target protein concentrations vary across samples, the conventional quantification methods cannot produce reliable results in downstream applications. In contrast, the ELISA we describe here consistently provides robust results.

biochemistry↗

bioRxiv2023

ACID: A Comprehensive Toolbox for Image Processing and Modeling of Brain, Spinal Cord, and Post-mortem Diffusion MRI Data

Diffusion MRI (dMRI) has become a crucial imaging technique in the field of neuroscience, with a growing number of clinical applications. Although most studies still focus on the brain, there is a growing interest in utilizing dMRI to investigate the healthy or injured spinal cord. The past decade has also seen the development of biophysical models that link MR-based diffusion measures to underlying microscopic tissue characteristics, which necessitates validation through ex vivo dMRI measurements. Building upon 13 years of research and development, we present an open-source, MATLAB-based academic software toolkit dubbed ACID: A Comprehensive Toolbox for Image Processing and Modeling of Brain, Spinal Cord, and Ex Vivo Diffusion MRI Data. ACID is an extension to the Statistical Parametric Mapping (SPM) software, designed to process and model dMRI data of the brain, spinal cord, and ex vivo specimens by incorporating state-of-the-art artifact correction tools, diffusion and kurtosis tensor imaging, and biophysical models that enable the estimation of microstructural properties in white matter. Additionally, the software includes an array of linear and non-linear fitting algorithms for accurate diffusion parameter estimation. By adhering to the Brain Imaging Data Structure (BIDS) data organization principles, ACID facilitates standardized analysis, ensures compatibility with other BIDS-compliant software, and aligns with the growing availability of large databases utilizing the BIDS format. Furthermore, being integrated into the popular SPM framework, ACID benefits from a wide range of segmentation, spatial processing, and statistical analysis tools as well as a large and growing number of SPM extensions. As such, this comprehensive toolbox covers the entire processing chain from raw DICOM data to group-level statistics, all within a single software package.

neuroscience↗

bioRxiv2023

Investigating apparent differences between standard DKI and axisymmetric DKI and its consequences for biophysical parameter estimates

PurposeIdentify differences between the acquisition-time efficient axisymmetric diffusion kurtosis imaging (DKI) model and standard DKI and their consequences on biophysical parameter estimates using standard DKI parameters as the ground truth. MethodsNoise-free, synthetic diffusion MRI (dMRI) human brain data are generated using standard DKI and fitted with axisymmetric DKI and standard DKI. Then, the five axisymmetric DKI tensor metrics (AxTM), the parallel and perpendicular diffusivity and kurtosis and mean of the kurtosis tensor, attainable with both DKI models are computed. Next, the five biophysical parameters axon water fraction and dispersion, extra axonal parallel and perpendicular diffusivity and intra axonal parallel diffusivity are estimated from the AxTM using the WMTI-Watson model. Finally, the number of substantially differing voxels (SDV), defined as voxels where estimation results of both DKI models differ more than 5%, is calculated for the AxTM and the biophysical parameters. ResultsFor the AxTM, the number of SDV was biggest for the parallel (26%) and perpendicular (51%) kurtosis while the other three AxTM had very few SDV (less than 5%). The biophysical parameters had much more SDV than the AxTM from which they were computed, ranging from 29% to 50%. ConclusionAxisymmetric DKI is a viable alternative to standard DKI in studies focusing on effects based on the parallel and perpendicular diffusion and mean of the kurtosis tensor. However, our findings urge caution when using axisymmetric DKI to investigate effects based on the parallel and perpendicular kurtosis or use it to estimate the biophysical parameters.

biophysics↗

bioRxiv2022

Development of a high-throughput barrier function assay using primary human gut organoids

Disruptions in the gut epithelial barrier can lead to the development of chronic indications such as inflammatory bowel disease (IBD). Historically, barrier function has been assessed in cancer cell lines, which do not contain all human intestinal cell types, leading to poor translatability. To bridge this gap, we adapted human primary gut organoids grown as monolayers to assess barrier function. In this work we describe and characterize a novel 96-well human gut organoid-derived monolayer system that enables medium/high-throughput quantitative assessment of candidate therapeutics. Normal human intestine differentiation patterns and barrier function were characterized and confirmed to recapitulate key aspects of in vivo biology. Next, cellular response to TNF- (a central driver of IBD) was determined using a diverse cadre of readouts.These outputs included transcription factor phosphorylation, target gene expression, cytokine/chemokine production, and barrier function. Additionally, we showed that TNF- pathway antagonists rescued damage caused by TNF- in a dose-dependent manner, indicating that this system is suitable for quantitative assessment of barrier modulating factors. Taken together, we have established a robust primary cell-based 96-well system capable of interrogating questions around mucosal response. This system is well suited to provide pivotal functional data to support translational target and drug discovery efforts.

immunology↗

bioRxiv2022

Epistatic effects between amino acid insertions and substitutions mediate toxin-resistance of vertebrate Na+,K+-ATPases

The recurrent evolution of resistance to cardiotonic steroids (CTS) across diverse animals most frequently involves convergent amino-acid substitutions to the H1-H2 extracellular loop of Na+,K+-ATPase (NKA). Previous work established that hystricognath rodents (e.g. chinchilla) and pterocliform birds (sandgrouse) have convergently evolved amino-acid insertions in the H1-H2 loop, but their functional significance is not known. Using protein engineering, we show that these insertions have distinct effects on CTS resistance of NKA in the two lineages that strongly depend on intramolecular interactions with other residues. Removing the insertion in the chinchilla lineage unexpectedly increases CTS resistance and decreases NKA activity. In the sandgrouse lineage, the insertion works in concert with the substitution Q111R to increase CTS resistance while maintaining wild-type ATPase activity levels. Molecular docking simulations provide additional insight into the biophysical mechanisms responsible for the context-specific CTS insensitivity of the enzyme. Our results highlight the diversity of genetic substrates that underlie CTS insensitivity in vertebrate NKA and reveal how amino-acid insertions can alter the phenotypic effects of point mutations at key sites in the same protein domain.

evolutionary biology↗

bioRxiv2022

The action of antimicrobial peptide LL37 is slow but effective against non-growing Escherichia coli cells

Antimicrobial peptides (AMPs) are amino-acid based antibiotics that primarily attack bacteria by perturbing their membranes. It has long been suggested that AMPs are effective against non-growing cells that tolerate conventional antibiotics. Despite recent advances in quantifying the action of AMPs at the single-cell level, we still do not have a clear picture of how this action is correlated with the physiology of target cells. Here we take complementary approaches, from single-cell and population-level experiments, to investigate the efficacy of human AMP LL37 against Escherichia coli cells at different growth phases. We first analyze time-lapse, single-cell data of the action of LL37 peptides on exponentially growing cells, which reveals that they act faster on long, dividing cells than on small, newborn cells. Next, we test the consequence of this cell-age dependence on the efficacy of LL37 against non-growing E. coli cells in stationary phase. We observe a consistent trend that the action of LL37 is, on average, {approx}5.0 minutes slower on non-growing cells as compared to that on exponentially growing cells. However, this difference in the rate of action is not reflected in the minimum bactericidal concentration (MBC) of LL37 peptides. Contrary to our expectation, the MBC measured for non-growing cells is smaller than that for exponentially growing cells, indicating that over a long period of time the LL37 peptides are more potent against non-growing cells. Author summaryAntibiotic treatments can fail due to regrowth of a bacterial subpopulation that start proliferation after the treatment is over. The regrowth is often from non-growing, dormant cells that persist the action of antibiotics without being resistant. In this work, we demonstrate that human antimicrobial peptide LL37 is potent against non-growing Escherichia coli cells.

microbiology↗

bioRxiv2022

Calibration allows accurate estimation of the axonal volume fraction with diffusion MRI

Biophysical models enable the non-invasive estimation of microstructural tissue features of the central nervous system such as the axonal volume fraction using diffusion weighted imaging (DWI)-data. However, these models trade accuracy with complexity and demands for time-efficient data acquisition. In this study, we hypothesise that their accuracy can be improved substantially through biophysically motivated, linear calibration. We test this hypothesis in the context of axonal volume fraction estimation in four different DWI-models of different complexity using multi-modal data including ex-vivo diffusion MRI- and electron microscopy (EM)-data in mice with broad dynamic range, whereby the latter served as gold standard. We found that two calibration parameters, an offset accounting for the fraction of unmyelinated axons in severely hypomyelinated mice and a scaling accounting for the compartment-specific relaxation, substantially improved the accuracy of axonal volume fraction. Furthermore, we theoretically predict the scaling parameter, and demonstrate that similar accuracy improvement can be achieved for a subset of DWI-models, if the scaling parameter is fixed to the predicted value instead of estimating it on basis of data. This is of practical relevance because it allows to estimate the remaining offset calibration parameter from a limited amount of multi-modal data and thus makes the proposed method usable in human brain data.

neuroscience↗

bioRxiv2022

Signalling speed along a key white matter tract influences memory recall ability in humans

Conduction velocity is the speed at which electrical signals travel along axons and is a crucial determinant of neural communication. Inferences about conduction velocity can now be made in vivo in humans using a measure called the magnetic resonance (MR) g-ratio. This is the ratio of the inner axon diameter relative to that of the axon plus the myelin sheath that encases it. Here, in the first application to cognition, we found that variations in MR g-ratio, and by inference conduction velocity, of the parahippocampal cingulum bundle were associated with autobiographical memory recall ability in 217 healthy adults. This tract connects the hippocampus with a range of other brain areas. We further observed that the association seemed to be with inner axon diameter rather than myelin content. The extent to which neurites were coherently organised within the parahippocampal cingulum bundle was also linked with autobiographical memory recall ability. Moreover, these findings were specific to autobiographical memory recall, and were not apparent for laboratory-based memory tests. Our results offer a new perspective on individual differences in autobiographical memory recall ability, highlighting the possible influence of specific features of white matter microstructure when recalling detailed memories of our real-life past experiences.

neuroscience↗