Biology subjects

Lotfi, A.

Publications and source records attributed to Lotfi, A..

5 recordsLinked to original sources

bioRxiv2026

Modeling behavior to disentangle motion-related effects in functional ultrasound imaging in awake, head-fixed mice

Functional ultrasound imaging (fUSI) enables brain-wide mapping of hemodynamic activity in awake rodents, offering a powerful bridge between systems neuroscience in animals and human neuroimaging. However, extending fUSI beyond tightly controlled sensory paradigms to more naturalistic behaviors is limited by motion-related confounds arising from locomotion, physiological arousal, and movement-linked neural activity. Here, we introduce a behavior-informed modeling framework that explicitly incorporates continuous measurements of running speed and head motion into a general linear model to account for motion-related variance while preserving interpretable task-related signals. We validate this approach in two head-fixed paradigms with distinct motion profiles: a visual stimulation task with minimal stimulus-driven movement, and a noxious stimulation task in which locomotion and arousal are intrinsic to the behavioral response. In both cases, explicit behavioral modeling recovers neural response patterns that more closely resemble low-motion reference conditions than blind, model-free denoising approaches. Critically, during noxious stimulation, behavior-informed modeling preserves shock-intensity-dependent activity in the primary somatosensory cortex that is attenuated by global component removal. These findings demonstrate that explicit modeling of behavior enables reliable interpretation of brain-wide fUSI signals during naturalistic, high-motion conditions, opening the door to studying affective and cognitive processes that were previously difficult to access with functional ultrasound imaging.

neuroscience↗

bioRxiv2025

S'Wipe: User-Friendly Stool Collection for High-Throughput Gut Metabolomics

Microbiome is increasingly recognized as a key factor in health. Intestinal microbiota modulates gut homeostasis via a range of diverse metabolites. For example, molecules such as short chain fatty acids (SCFAs), the microbial fermentation products of dietary fiber, have been established to be reflective of microbiome and/or dietary shifts and SCFAs alterations have been linked to multiple gastrointestinal disorders from cancer to colitis. Despite their potential as biomarkers, technical challenges in stool collection have limited clinical translation. Here we present Stool Wipe (SWipe), an ultra-low-cost fecal collection method using lint-free, mass spectrometry-compatible cellulose wipes as toilet paper. Specimens are preserved in ethanol without refrigeration and can be shipped via regular mail. Mass spectrometry analysis demonstrated that SWipe captures both volatile and non-volatile metabolites with reproducibility and stability validated for diagnostically relevant molecules. We show that SWipe performs equivalently to direct stool collection, enabling interchangeable use and comparison with existing studies. This methodology is ideally suited for large-scale population studies, longitudinal tracking, and personalized medicine applications. IMPORTANCEGut microbiome and intestinal metabolome present invaluable diagnostic and therapeutic targets. However, conventional stool testing has several barriers limiting bioassessment from populations. Routine, high temporal resolution monitoring of stool metabolome, including extensively validated and broadly informative biomarkers such as short chain fatty acids (SCFAs), is not implemented due to relatively high cost and inconvenience of sampling, possible need for clinical setting for sample collection, difficulty to collect samples reproducibly, especially due to potential for user errors, requirement for freezer storage and maintaining cold chain during shipment. We present a sampling strategy specifically designed to overcome these obstacles. We demonstrate how this method can enable capturing accurate molecular snapshots at massive scales, at ultra low cost. The approach collapses complex medical-grade collection into easy self-administration. Individuals can thereby self-monitor therapeutic responses through routine metabolome tracking, including the volatilome, otherwise hindered by infrastructure restrictions. Ultimately, this sampling approach is intended to enable participatory wellness transformation through practical high frequency self-sampling.

biochemistry↗

bioRxiv2024

Ordering molecular diversity in untargeted metabolomics via molecular community networking

Natures molecular diversity is not random but displays intricate organization stemming from biological necessity. Molecular networking connects metabolites with structural similarity, enabling molecular discoveries from mass spectrometry data using arbitrary similarity thresholds that can fracture natural metabolite families. We present molecular community networking (MCN), that optimizes connectivity for each metabolite, rescuing lost relationships and capturing otherwise "hidden" metabolite connections. Using MCN, we demonstrate the discovery of novel dipeptide-conjugated bile acids.

biochemistry↗

bioRxiv2024

Spatial chemistry of citrus reveals molecules bactericidal to Candidatus Liberibacter asiaticus

Huanglongbing (HLB), associated with the psyllid-vectored phloem-limited bacterium, Candidatus Liberibacter asiaticus (CLas), is a disease threat to all citrus production worldwide. Currently, there are no sustainable curative or prophylactic treatments available. In this study, we utilized mass spectrometry (MS)-based metabolomics in combination with 3D molecular mapping to visualize complex chemistries within plant tissues to explore how these chemistries change in vivo in HLB-impacted trees. We demonstrate how spatial information from molecular maps of branches and single leaves yields insight into the biology not accessible otherwise. In particular, we found evidence that flavonoid biosynthesis is disrupted in HLB-impacted trees, and an increase in the polyamine, feruloylputrescine, is highly correlated with an increase in disease severity. Based on mechanistic details revealed by these molecular maps, followed by metabolic modeling, we formulated and tested the hypothesis that CLas infection either directly or indirectly converts the precursor compound, ferulic acid, to feruloylputrescine to suppress the antimicrobial effects of ferulic acid and biosynthetically downstream flavonoids. Using in vitro bioassays, we demonstrated that ferulic acid and bioflavonoids are indeed highly bactericidal to CLas, with the activity on par with a reference antibiotic, oxytetracycline, recently approved for HLB management. We propose these compounds should be evaluated as therapeutics alternatives to the antibiotics for HLB treatment. Overall, the utilized 3D metabolic mapping approach provides a promising methodological framework to identify pathogen-specific inhibitory compounds in planta for potential prophylactic or therapeutic applications.

plant biology↗

bioRxiv2024

S-Wipe: stool sample collection for metabolomic gut health tracking

Microbiome is increasingly recognized as a key factor in health. Intestinal microbiota modulates gut homeostasis via a range of diverse metabolites. Molecules such as short chain fatty acids (SCFAs), the microbial fermentation products of dietary fiber, have been established to be reflective of microbiome and/or dietary shifts and have been linked to multiple gastrointestinal disorders from cancer to colitis, and thus present an excellent diagnostic target. Yet, technical bottlenecks preclude broad translation of such established biomarkers into routine medical practice. In particular, easily accessible, reproducible and robust sampling of stool remains challenging. Here we present Stool Wipe (S-Wipe), an ultra low cost, simplified fecal specimen collection approach designed to overcome key translational barriers without compromising analytical rigor. This sampling approach harnesses lint-free mass spectrometry-compatible cellulose wipes used as a regular toilet paper. The collected stool specimens are then preserved in ethanol solution, do not require refrigeration and can be shipped via regular mail. Using mass spectrometry, we have demonstrated a broad range of captured metabolites, both volatile and non-volatile. The reproducibility and stability of the method was validated for a panel of molecules of particular diagnostic interest, including SCFAs and p-cresol. We demonstrate sensitivity as well as stability and reproducibility of various metabolites collected with S-Wipe. We further demonstrate that S-Wipe is equivalent to the direct stool collection and thus could be used interchangeably and compared to other studies where stool is collected directly. This methodology is ideally suited and is scalable for broad population-based studies, longitudinal tracking such as therapeutic interventions and personalized medicine. IMPORTANCEGut microbiome and intestinal metabolome present invaluable diagnostic and therapeutic targets. However, conventional stool testing has several barriers limiting bioassessment from populations. Routine, high temporal resolution monitoring of stool metabolome, including validated biomarkers such as SCFAs, is not implemented due to relatively high cost and inconvenience of sampling, possible need for clinical setting for sample collection, difficulty to collect samples reproducibly, especially due to possible user errors, requirement for freezer storage and maintaining cold chain during shipment. We present a sampling strategy specifically designed to overcome these obstacles. This method can enable capturing accurate molecular snapshots at massive scales, at ultra low cost. The approach collapses complex medical-grade collection into easy self-administration. Individuals can thereby self-monitor therapeutic responses through routine metabolome tracking, including the volatilome, otherwise hindered by infrastructure restrictions. Ultimately, this sampling approach is intended to enable participatory wellness transformation through practical high frequency self-sampling.

biochemistry↗