Biology subjects

Hashemi, M.

Publications and source records attributed to Hashemi, M..

32 records · Page 2Linked to original sources

bioRxiv2023

Probing the Mechanisms of Global Brain Reconfiguration after Local Manipulations

Understanding how localized brain interventions translate into whole-brain dynamics is crucial for deciphering neural function and tailoring therapeutic strategies. Combining mouse experimental datasets of focal interventions (thalamic lesion and chemogenetic silencing of cortical hubs), we demonstrate both local and global effects. Using whole-brain simulations of experimental data, we not only confirm the distributed nature of local manipulations but also offer mechanistic insights into these processes. Our simulations predict specific alterations in firing rates and spectral characteristics across specific brain networks, leading to structured changes in functional connectivity patterns. Some of these predictions have been empirically validated. Notably, the affected brain subnetworks--and their resultant signatures of change--are contingent on the original intervention site, suggesting a method to accurately localize the source of alteration. Our results provide a general framework for interpreting localized intervention effects, offering insights that could refine clinical interventions for focal brain disorders by enabling targeted circuit-level neuromodulation strategies.

neuroscience↗

bioRxiv2023

Mixed data analysis detected Endocrine Fibroblast Growth Factors (FGF19, FGF21, and FGF23) as Prognostic and Diagnostic Markers of Colorectal Neoplasia and Carcinoma

BackgroundEndocrine fibroblast growth factors (eFGFs) play important roles in various cellular signaling processes such as development and differentiation. These genes were also found to be significantly related to several cancer. However, little is known about the role of eFGFs in colon neoplasia and colon adenocarcinoma (COAD). MethodsWe performed systematically and comprehensively investigated the gene expression, DNA methylation, prognostic significance, genetic alteration, co-expressed genes, protein-protein interaction, small molecules pathway, and drug interactions of eFGFs based on the TIMER2.0, GEPIA2, UALCAN, OncoDB, cBioPortal, LinkedOmics, STRING, SMPDB, htfTarget, mirTarBase, circBank and DGIdb databases. Ultimately, the correlations of eFGFs expressions between polyp and COAD tissues compared to normal mucosa were validated using qRT-PCR as a cross-sectional part of our study. ResultsThe results indicated that eFGFs are highly expressed in COAD, and abnormal gene expressions may be related to promoter methylation. In this matter, methylation analysis revealed promotor hypermethylation of FGF19 and FGF21. Conversely, FGF23 was shown to have a tendency for promotor hypomethylation. Moreover, hypermethylation of FGF21 and FGF23 and downregulation of FGF23 were found to be detrimental to the survival of COAD patients. KEGG pathway analyses indicated that the co-expressed genes of eFGF family members were mainly related to the regulation of the actin cytoskeleton and, more notably, in Ras signaling, PI3k-Akt signaling, Rap1 signaling, and cancer pathways. Based on qRT-PCR results, FGF21 was significantly overexpressed in the colon polyps compared to normal mucosa. Additionally, RNA expression of FGF21 and FGF23 was markedly elevated in adenomatous polyps as opposed to hyperplastic polyps. ConclusionCollectively, these findings reveal the critical roles of eFGFs in COAD tumorigenesis and suggest eFGF family members as promising prognostic and diagnostic markers for CRC as well as discriminating markers for high-risk from low-risk polyps.

bioinformatics↗

bioRxiv2023

Estimating multiplicity of infection, allele frequencies, and prevalences accounting for incomplete data

BackgroundMolecular surveillance of infectious diseases allows the monitoring of pathogens beyond the granularity of traditional epidemiological approaches and is well-established for some of the most relevant infectious diseases such as malaria. The presence of genetically distinct pathogenic variants within an infection, referred to as multiplicity of infection (MOI) or complexity of infection (COI) is common in malaria and similar infectious diseases. It is an important metric that scales with transmission intensities, potentially affects the clinical pathogenesis, and a confounding factor when monitoring the frequency and prevalence of pathogenic variants. Several statistical methods exist to estimate MOI and the frequency distribution of pathogen variants. However, a common problem is the quality of the underlying molecular data. If molecular assays fail not randomly, it is likely to underestimate MOI and the prevalence of pathogen variants. Methods and findingsA statistical model is introduced which explicitly addresses data quality, by assuming a probability by which a pathogen variant remains undetected in a molecular assay. This is different from the assumption of missing at random, for which a molecular assay either performs perfectly or fails completely. The method is applicable to a single molecular marker and allows to estimate allele-frequency spectra, the distribution of MOI, and the probability of variants to remain undetected (incomplete information). Based on the statistical model, expressions for the prevalence of pathogen variants are derived and differences between frequency and prevalence are discussed. The usual desirable asymptotic properties of the maximum-likelihood estimator (MLE) are established by rewriting the model into an exponential family. The MLE has promising finite sample properties in terms of bias and variance. The covariance matrix of the estimator is close to the Cramer-Rao lower bound (inverse Fisher information). Importantly, the estimators variance is larger than that of a similar method which disregards incomplete information, but its bias is smaller. ConclusionsAlthough the model introduced here has convenient properties, in terms of the mean squared error it does not outperform a simple standard method that neglects missing information. Thus, the new method is recommendable only for data sets in which the molecular assays produced poor quality results. This will be particularly true if the model is extended to accommodate information from multiple molecular markers at the same time, and incomplete information at one or more markers leads to strong depletion of sample size.

molecular biology↗

bioRxiv2023

Assembly of Synaptic Protein-DNA Complexes: Critical Role of Non-Specific Interactions

The synaptic protein-DNA complexes, formed by specialized proteins that bridge two or more distant sites on DNA, are critically involved in various genetic processes. However, the molecular mechanism by which the protein searches for these sites and how it brings them together is not well understood. Our previous studies directly visualized search pathways used by SfiI, and we identified two pathways, DNA threading and site-bound transfer pathways, specific to the site search process for synaptic DNA-protein systems. To investigate the molecular mechanism behind these site search pathways, we assembled complexes of SfiI with various DNA substrates corresponding to different transient states and measured their stability using a single-molecule fluorescence approach. These assemblies corresponded to specific-specific (synaptic), non-specific-non-specific (non-specific), and specific-non-specific (pre-synaptic) SfiI-DNA states. Unexpectedly, there was an elevated stability in pre-synaptic complexes assembled with specific and non-specific DNA substrates has been found. To explain these surprising observations, a theoretical approach that describes the assembly of these complexes and compares the predictions with the experiment is developed. The theory explains this effect by utilizing entropic arguments, according to which, after the partial dissociation, the non-specific DNA template has multiple possibilities of rebinding, effectively increasing the stability. Such difference in the stabilities of SfiI complexes with specific and non-specific DNA explains the utilization of threading and site-bound transfer pathways in the search process of synaptic protein-DNA complexes discovered in the time-lapse AFM experiments.

biophysics↗

bioRxiv2022

Bayesian Pharmacometrics Analysis of Baclofen for Alcohol Use Disorder

Alcohol use disorder (AUD) also called alcohol dependence is a major public health problem, which affects almost 10% of the worlds population. Baclofen as a selective GABAB receptor agonist has emerged as a promising drug for the treatment of AUD, however, its optimal dosage varies according to individuals, and its exposure-response relationship has not been well established yet. In this study, we use a principled Bayesian workflow to estimate the parameters of a pharmacokinetic (PK) population model from Baclofen administration to patients with AUD. By monitoring various convergence diagnostics, the probabilistic methodology is first validated on synthetic longitudinal datasets and then, applied to infer the PK model parameters based on the clinical data that were retrospectively collected from outpatients treated with oral Baclofen. We show that state-of-the-art advances in automatic Bayesian inference using self-tuning Hamiltonian Monte Carlo (HMC) algorithms with a leveraged level of information in priors provide accurate predictions on Baclofen plasma concentration in individuals. This approach may pave the way to render non-parametric HMC sampling methods sufficiently easy and reliable to use in clinical schedules for personalized treatment of AUD.

pharmacology and toxicology↗

bioRxiv2022

Sequence Dependent Internucleosomal Interactions Dominate Array Assembly

The organization of the nucleosome array is a critical component of the chromatin assembly into higher order structure as well as its function. Here we investigated the contribution of the DNA sequence and internucleosomal interactions to the organization of the nucleosomal arrays in compact structures using Atomic Force Microscopy. We assembled nucleosomes on DNA substrates allowing for the formation of tetranucleosomes. We found that nucleosomes are capable of forming constructs with the close positioning of nucleosomes with no discernible space between them, even in the case of assembled dinucleosomes. This morphology of the array is in contrast with that observed for arrays assembled with repeats of the nucleosome positioning motifs separated by uniform spacers. Simulated assembly of tetranucleosomes by random placement along the substrates revealed that nucleosome array compaction is promoted by the interaction of the nucleosomes. We developed a theoretical model to account for the role of DNA sequence and internucleosomal interactions in the formation of the nucleosome structures. These findings suggest that, in the chromatin assembly, the affinity of the nucleosomes to the DNA sequence and the strengths of the internucleosomal interactions are the two major factors defining the compactness of the chromatin.

biophysics↗

bioRxiv2022

The virtual aging brain: a model-driven explanation for cognitive decline in older subjects

Healthy aging is accompanied by heterogeneous decline of cognitive abilities among individuals, especially during senescence. The mechanisms of this variability are not understood, but have been associated with the reorganization of white matter fiber tracts and the functional co-activations of brain regions. Here, we built a causal inference framework to provide mechanistic insight into the link between structural connectivity and brain function, informed by brain imaging data and network modeling. By applying various degrees of interhemispheric degradation of structural connectivity, we were not only able to reproduce the age-related decline in interhemispheric functional communication and the associated dynamical flexibility, but we obtained an increase of global modulation of structural connectivity over the brain function during senescence. Notably, the increase in modulation between structural connectivity and brian function was higher in magnitude and steeper in its increase in older adults with poor cognitive performance. We independently validated the causal hypothesis of our framework via a Bayesian approach based on deep-learning. The current results might be the first mechanistic demonstration of dedifferentiation and scaffolding during aging leading to cognitive decline demonstrated in a large cohort.

neuroscience↗

bioRxiv2021

Parameter inference on brain network models with unknown node dynamics and spatial heterogeneity

Model-based data analysis of whole-brain dynamics links the observed data to model parameters in a network of neural masses. In recent years a special focus was placed on the role of regional variance of model parameters for the emergent activity. Such analyses however depend on the properties of the employed neural mass model, which is often obtained through a series of major simplifications or analogies. Here we propose a data-driven approach where the neural mass model needs not to be specified. Building on the recent progresses in identification of dynamical systems with neural networks, we propose a method to infer from the functional data both the neural mass model representing the regional dynamics as well as the region- and subject-specific parameters, while respecting the known network structure. We demonstrate on two synthetic data sets that our method is able to recover the original model parameters, and that the trained generative model produces dynamics resembling the training data both on the regional level and on the whole-brain level. We further apply the method to resting-state fMRI data from Human Connectome Project. We find that to achieve best fit, the model needs two dimensional state space and three regional parameters, one of which is strongly correlated with the map of genetic expression in human brain. The present approach opens a novel way to the analysis of resting-state fMRI with possible applications in understanding the changes of whole-brain dynamics during aging or in neurodegenerative diseases.

neuroscience↗

bioRxiv2021

Restriction of RecG translocation by DNA mispairing

The RecG DNA helicase plays a crucial role in stalled replication fork rescue as the guardian of the bacterial genome. We have recently demonstrated that single-strand DNA binding protein (SSB) promotes binding of RecG to the stalled replication fork by remodeling RecG, enabling the helicase to translocate ahead of the fork. We also hypothesized that mispairing of DNA could limit such translocation of RecG, which plays the role of roadblocks for the fork movement. Here, we used atomic force microscopy (AFM) to directly test this hypothesis and investigate how sensitive RecG translocation is to different types of mispairing. We found that a C-C mismatch at a distance of 30 bp away from the fork position prevents translocation of RecG over this mispairing. A G-bulge placed at the same distance also has a similar roadblock efficiency. However, a C-C mismatch 10 bp away from the fork does not prevent RecG translocation, as 10 bp from fork is within the distance of footprint of RecG on fork DNA. Our findings suggest that retardation of RecG translocation ahead of the replication fork can be a mechanism for the base pairing control for DNA replication machinery.

biophysics↗

bioRxiv2020

Cholesterol in membranes facilitates aggregation of amyloid beta protein at physiologically low concentrations

The formation of amyloid {beta} (1-42) (A{beta}42) oligomers is considered to be a critical step in the development of Alzheimers disease (AD). However, the mechanism underlying this process at physiologically low concentrations of A{beta}42 remains unclear. We have previously shown that oligomers assemble at such low A{beta}42 monomer concentrations in vitro on phospholipid membranes. We hypothesized that membrane composition is the factor controlling the aggregation process. Accumulation of cholesterol in membranes is associated with AD development, suggesting that insertion of cholesterol into membranes may initiate the A{beta}42 aggregation, regardless of a low monomer concentration. We used atomic force microscopy (AFM) to directly visualize the aggregation process of A{beta}42 on the surface of a lipid bilayer containing cholesterol. Time-lapse AFM imaging unambiguously demonstrates that cholesterol in the lipid bilayer significantly enhances the aggregation process of A{beta}42 at nanomolar monomer concentration. Quantitative analysis of the AFM data shows that both the number of A{beta}42 oligomers and their sizes grow when cholesterol is present. Importantly, the aggregation process is dynamic, so the aggregates assembled on the membrane can dissociate from the bilayer surface into the bulk solution. Computational modeling demonstrated that the lipid bilayer containing cholesterol had an elevated affinity to A{beta}42. Moreover, monomers adopted the aggregation-prone conformations present in amyloid fibrils. The low energy barriers between these conformations facilitate the transition between monomer states and is another factor promoting the self-association of the monomers.

biophysics↗

bioRxiv2019

Spontaneous Self-assembly of Amyloid β (1-40) into Dimers

The self-assembly and fibrillation of amyloid {beta} (A{beta}) proteins is the neuropathological hallmark of Alzheimers disease. However, the molecular mechanism of how disordered monomers assemble into aggregates remains largely unknown. In this work, we characterize the assembly of A{beta} (1-40) monomers into dimers using long-time molecular dynamics simulations. Upon interaction, the monomers undergo conformational transitions, accompanied by change of the structure, leading to the formation of a stable dimer. The dimers are primarily stabilized by interactions in the N-terminal region (residues 5-12), in the central hydrophobic region (residues 16-23), and in the C-terminal region (residues 30-40); with inter-peptide interactions focused around the N- and C- termini. The dimers do not contain long {beta}-strands that are usually found in fibrils.

biophysics↗

bioRxiv2019

Lipid membranes trigger misfolding and self-assembly of amyloid β 42 protein into aggregates

The assembly of polypeptides and proteins into nanoscale aggregates is a phenomenon observed in a vast majority of proteins. Importantly, aggregation of amyloid {beta} (A{beta}) proteins is considered as a major cause for the development of Alzheimers disease. The process depends on various conditions and typical test-tube experiments require high protein concentration that complicates the translation of results obtained in vitro to understanding the aggregation process in vivo. Here we demonstrate that A{beta}42 monomers at the membrane bilayer are capable of self-assembling into aggregates at physiologically low concentrations, and the membrane in this aggregation process plays a role of a catalyst. We applied all-atom molecular dynamics to demonstrate that the interaction with the membrane surface dramatically changes the conformation of A{beta}42 protein. As a result, the misfolded A{beta}42 rapidly assembles into dimers, trimers and tetramers, so the on-surface aggregation is the mechanism by which amyloid oligomers are produced and spread.

neuroscience↗

bioRxiv2018

Phospholipid membranes promote the early stage assembly of α-synuclein aggregates

Development of Parkinsons disease is associated with spontaneous self-assembly of -synuclein (-syn). Efforts aimed at understanding this process have produced little clarity and the mechanism remains elusive. We report a novel effect of phospholipid bilayers on the catalysis of -syn aggregation from monomers. We directly visualized -syn aggregation on supported lipid bilayers using time-lapse atomic force microscopy. We discovered that -syn assemble in aggregates on bilayer surfaces even at the nanomolar concentration of monomers in solution. The efficiency of the aggregation process depends on the membrane composition, being highest for a negatively charged bilayer. Furthermore, assembled aggregates can dissociate from the surface, suggesting that on-surface aggregation can be a mechanism by which pathological aggregates are produced. Computational modeling revealed that interaction of -syn with bilayer surface changes the protein conformation and its affinity to assemble into dimers, and these properties depend on the bilayer composition. A model of the membrane-mediated aggregation triggering the assembly of neurotoxic aggregates is proposed.

neuroscience↗

bioRxiv2017

Nanoscale Dynamics of Centromere Nucleosomes and the Critical Roles of CENP-A

In the absence of a functioning centromere, chromosome segregation becomes aberrant, leading to an increased rate of aneuploidy. The highly specific recognition of centromeres by kinetochores suggests that specific structural characteristics define this region, however, the structural details and mechanism underlying this recognition remains a matter of intense investigation. To address this, High speed atomic force microscopy was used for direct visualization of the spontaneous dynamics of CENP-A nucleosomes at the sub-second time scale. We report that CENP-A nucleosomes change conformation spontaneously and reversibly, utilizing two major pathways: unwrapping, and looping of the DNA; enabling core transfer between neighboring DNA substrates. Along with these nucleosome dynamics we observed that CENP-A stabilizes the histone core against dissociating to histone subunits, unique from H3 cores which are only capable of such plasticity in the presence of remodeling factors. These findings have implications for the dynamics and integrity of nucleosomes at the centromere.

biophysics↗