47 results on '"Sindi, Suzanne S."'
Search Results
2. Studying the Effects of Oral Contraceptives on Coagulation Using a Mathematical Modeling Approach
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Kent, Amy, Leiderman, Karin, Nelson, Anna C., Sindi, Suzanne S., Stadt, Melissa M., Xiong, Lingyun (Ivy), Zhang, Ying, Spirn, Daniel, Series Editor, Ford Versypt, Ashlee N., editor, Segal, Rebecca A., editor, and Sindi, Suzanne S., editor
- Published
- 2024
- Full Text
- View/download PDF
3. A Computational Workflow for Analysis of 3′ Tag‐Seq Data
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Paropkari, Akshay D, Bapat, Priyanka S, Sindi, Suzanne S, and Nobile, Clarissa J
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Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Biotechnology ,Cancer Genomics ,Cancer ,Bioengineering ,Networking and Information Technology R&D (NITRD) ,Human Genome ,Gene Expression Profiling ,Workflow ,Software ,RNA-Seq ,RNA ,Messenger ,computational pipeline ,differential gene expression ,RNA sequencing ,' Tag-Seq ,3′ Tag-Seq - Abstract
RNA-sequencing (RNA-seq) is a gold-standard method to profile genome-wide changes in gene expression. RNA-seq uses high-throughput sequencing technology to quantify the amount of RNA in a biological sample. With the increasing popularity of RNA-seq, many variations on the protocol have been proposed to extract unique and relevant information from biological samples. 3' Tag-Seq (also called TagSeq, 3' Tag-RNA-Seq, and Quant-Seq 3' mRNA-Seq) is one RNA-seq variation where the 3' end of the transcript is selected and amplified to yield one copy of cDNA from each transcript in the biological sample. We present a simple, easy-to-use, and publicly available computational workflow to analyze 3' Tag-Seq data. The workflow begins by trimming sequence adapters from raw FASTQ files. The trimmed sequence reads are checked for quality using FastQC and aligned to the reference genome, and then read counts are obtained using STAR. Differential gene expression analysis is performed using DESeq2, based on differential analysis of gene count data. The outputs of this workflow are MA plots, tables of differentially expressed genes, and UpSet plots. This protocol is intended for users specifically interested in analyzing 3' Tag-Seq data, and thus normalizations based on transcript length are not performed within the workflow. Future updates to this workflow could include custom analyses based on the gene counts table as well as data visualization enhancements. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Running the 3' Tag-Seq workflow Support Protocol: Generating genome indices.
- Published
- 2023
4. Modeling and Global Sensitivity Analysis of Strategies to Mitigate Covid-19 Transmission on a Structured College Campus
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Zhao, Lihong, Santiago, Fabian, Rutter, Erica M, Khatri, Shilpa, and Sindi, Suzanne S
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Biological Sciences ,Emerging Infectious Diseases ,Immunization ,Vaccine Related ,Infectious Diseases ,Prevention ,Infection ,Good Health and Well Being ,Humans ,COVID-19 ,Pandemics ,SARS-CoV-2 ,Mathematical Concepts ,Models ,Biological ,ODE ,SEIR ,Global sensitivity analysis ,Sobol indices ,Mathematical Sciences ,Bioinformatics ,Biological sciences ,Mathematical sciences - Abstract
In response to the COVID-19 pandemic, many higher educational institutions moved their courses on-line in hopes of slowing disease spread. The advent of multiple highly-effective vaccines offers the promise of a return to "normal" in-person operations, but it is not clear if-or for how long-campuses should employ non-pharmaceutical interventions such as requiring masks or capping the size of in-person courses. In this study, we develop and fine-tune a model of COVID-19 spread to UC Merced's student and faculty population. We perform a global sensitivity analysis to consider how both pharmaceutical and non-pharmaceutical interventions impact disease spread. Our work reveals that vaccines alone may not be sufficient to eradicate disease dynamics and that significant contact with an infectious surrounding community will maintain infections on-campus. Our work provides a foundation for higher-education planning allowing campuses to balance the benefits of in-person instruction with the ability to quarantine/isolate infectious individuals.
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- 2023
5. Inferring gene regulatory networks using transcriptional profiles as dynamical attractors
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Li, Ruihao, Rozum, Jordan C, Quail, Morgan M, Qasim, Mohammad N, Sindi, Suzanne S, Nobile, Clarissa J, Albert, Réka, and Hernday, Aaron D
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Biochemistry and Cell Biology ,Bioinformatics and Computational Biology ,Genetics ,Biological Sciences ,Bioengineering ,Human Genome ,Generic health relevance ,Bayes Theorem ,Gene Regulatory Networks ,Algorithms ,Biological Evolution ,Candida albicans ,RNA ,Messenger ,Mathematical Sciences ,Information and Computing Sciences ,Bioinformatics - Abstract
Genetic regulatory networks (GRNs) regulate the flow of genetic information from the genome to expressed messenger RNAs (mRNAs) and thus are critical to controlling the phenotypic characteristics of cells. Numerous methods exist for profiling mRNA transcript levels and identifying protein-DNA binding interactions at the genome-wide scale. These enable researchers to determine the structure and output of transcriptional regulatory networks, but uncovering the complete structure and regulatory logic of GRNs remains a challenge. The field of GRN inference aims to meet this challenge using computational modeling to derive the structure and logic of GRNs from experimental data and to encode this knowledge in Boolean networks, Bayesian networks, ordinary differential equation (ODE) models, or other modeling frameworks. However, most existing models do not incorporate dynamic transcriptional data since it has historically been less widely available in comparison to "static" transcriptional data. We report the development of an evolutionary algorithm-based ODE modeling approach (named EA) that integrates kinetic transcription data and the theory of attractor matching to infer GRN architecture and regulatory logic. Our method outperformed six leading GRN inference methods, none of which incorporate kinetic transcriptional data, in predicting regulatory connections among TFs when applied to a small-scale engineered synthetic GRN in Saccharomyces cerevisiae. Moreover, we demonstrate the potential of our method to predict unknown transcriptional profiles that would be produced upon genetic perturbation of the GRN governing a two-state cellular phenotypic switch in Candida albicans. We established an iterative refinement strategy to facilitate candidate selection for experimentation; the experimental results in turn provide validation or improvement for the model. In this way, our GRN inference approach can expedite the development of a sophisticated mathematical model that can accurately describe the structure and dynamics of the in vivo GRN.
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- 2023
6. N-ACT: An Interpretable Deep Learning Model for Automatic Cell Type and Salient Gene Identification
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Heydari, A. Ali, Davalos, Oscar A., Hoyer, Katrina K., and Sindi, Suzanne S.
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Quantitative Biology - Genomics ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Single-cell RNA sequencing (scRNAseq) is rapidly advancing our understanding of cellular composition within complex tissues and organisms. A major limitation in most scRNAseq analysis pipelines is the reliance on manual annotations to determine cell identities, which are time consuming, subjective, and require expertise. Given the surge in cell sequencing, supervised methods-especially deep learning models-have been developed for automatic cell type identification (ACTI), which achieve high accuracy and scalability. However, all existing deep learning frameworks for ACTI lack interpretability and are used as "black-box" models. We present N-ACT (Neural-Attention for Cell Type identification): the first-of-its-kind interpretable deep neural network for ACTI utilizing neural-attention to detect salient genes for use in cell-type identification. We compare N-ACT to conventional annotation methods on two previously manually annotated data sets, demonstrating that N-ACT accurately identifies marker genes and cell types in an unsupervised manner, while performing comparably on multiple data sets to current state-of-the-art model in traditional supervised ACTI.
- Published
- 2022
7. Genome-wide Profiling of Transcription Factor-DNA Binding Interactions in Candida albicans: A Comprehensive CUT&RUN Method and Data Analysis Workflow.
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Qasim, Mohammad N, Valle Arevalo, Ashley, Paropkari, Akshay D, Ennis, Craig L, Sindi, Suzanne S, Nobile, Clarissa J, and Hernday, Aaron D
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Microbiology ,Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Human Genome ,1.1 Normal biological development and functioning ,2.1 Biological and endogenous factors ,2.2 Factors relating to the physical environment ,Generic health relevance ,Candida albicans ,DNA ,Data Analysis ,Endonucleases ,High-Throughput Nucleotide Sequencing ,Humans ,Transcription Factors ,Workflow ,Biochemistry and Cell Biology ,Psychology ,Cognitive Sciences ,Biochemistry and cell biology - Abstract
Regulatory transcription factors control many important biological processes, including cellular differentiation, responses to environmental perturbations and stresses, and host-pathogen interactions. Determining the genome-wide binding of regulatory transcription factors to DNA is essential to understanding the function of transcription factors in these often complex biological processes. Cleavage under targets and release using nuclease (CUT&RUN) is a modern method for genome-wide mapping of in vivo protein-DNA binding interactions that is an attractive alternative to the traditional and widely used chromatin immunoprecipitation followed by sequencing (ChIP-seq) method. CUT&RUN is amenable to a higher-throughput experimental setup and has a substantially higher dynamic range with lower per-sample sequencing costs than ChIP-seq. Here, a comprehensive CUT&RUN protocol and accompanying data analysis workflow tailored for genome-wide analysis of transcription factor-DNA binding interactions in the human fungal pathogen Candida albicans are described. This detailed protocol includes all necessary experimental procedures, from epitope tagging of transcription factor-coding genes to library preparation for sequencing; additionally, it includes a customized computational workflow for CUT&RUN data analysis.
- Published
- 2022
8. AddTag, a two-step approach with supporting software package that facilitates CRISPR/Cas-mediated precision genome editing
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Seher, Thaddeus D, Nguyen, Namkha, Ramos, Diana, Bapat, Priyanka, Nobile, Clarissa J, Sindi, Suzanne S, and Hernday, Aaron D
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Biological Sciences ,Genetics ,Biotechnology ,Human Genome ,Good Health and Well Being ,CRISPR-Cas Systems ,Gene Editing ,Genetic Engineering ,Genomics ,Software ,Cas9 ,RNA-guided nuclease ,homology-directed repair ,genetic complementation ,Candida albicans ,Biochemistry and cell biology ,Statistics - Abstract
CRISPR/Cas-induced genome editing is a powerful tool for genetic engineering, however, targeting constraints limit which loci are editable with this method. Since the length of a DNA sequence impacts the likelihood it overlaps a unique target site, precision editing of small genomic features with CRISPR/Cas remains an obstacle. We introduce a two-step genome editing strategy that virtually eliminates CRISPR/Cas targeting constraints and facilitates precision genome editing of elements as short as a single base-pair at virtually any locus in any organism that supports CRISPR/Cas-induced genome editing. Our two-step approach first replaces the locus of interest with an "AddTag" sequence, which is subsequently replaced with any engineered sequence, and thus circumvents the need for direct overlap with a unique CRISPR/Cas target site. In this study, we demonstrate the feasibility of our approach by editing transcription factor binding sites within Candida albicans that could not be targeted directly using the traditional gene-editing approach. We also demonstrate the utility of the AddTag approach for combinatorial genome editing and gene complementation analysis, and we present a software package that automates the design of AddTag editing.
- Published
- 2021
9. Nucleation seed size determines amyloid clearance and establishes a barrier to prion appearance in yeast
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Villali, Janice, Dark, Jason, Brechtel, Teal M, Pei, Fen, Sindi, Suzanne S, and Serio, Tricia R
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Biochemistry and Cell Biology ,Biological Sciences ,Dementia ,Brain Disorders ,Neurodegenerative ,Rare Diseases ,Neurosciences ,Transmissible Spongiform Encephalopathy (TSE) ,Acquired Cognitive Impairment ,Emerging Infectious Diseases ,Infectious Diseases ,Underpinning research ,Aetiology ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Amyloid ,Cycloheximide ,Heat-Shock Proteins ,Peptide Termination Factors ,Prions ,Saccharomyces cerevisiae ,Saccharomyces cerevisiae Proteins ,Chemical Sciences ,Medical and Health Sciences ,Biophysics ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences ,Chemical sciences - Abstract
Amyloid appearance is a rare event that is promoted in the presence of other aggregated proteins. These aggregates were thought to act by templating the formation of an assembly-competent nucleation seed, but we find an unanticipated role for them in enhancing the persistence of amyloid after it arises. Specifically, Saccharomyces cerevisiae Rnq1 amyloid reduces chaperone-mediated disassembly of Sup35 amyloid, promoting its persistence in yeast. Mathematical modeling and corresponding in vivo experiments link amyloid persistence to the conformationally defined size of the Sup35 nucleation seed and suggest that amyloid is actively cleared by disassembly below this threshold to suppress appearance of the [PSI+] prion in vivo. Remarkably, this framework resolves multiple known inconsistencies in the appearance and curing of yeast prions. Thus, our observations establish the size of the nucleation seed as a previously unappreciated characteristic of prion variants that is key to understanding transitions between prion states.
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- 2020
10. Host tracheal and intestinal microbiomes inhibit Coccidioides growth in vitro
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Tejeda-Garibay, Susana, primary, Zhao, Lihong, additional, Hum, Nicholas R., additional, Pimentel, Maria, additional, Diep, Anh L., additional, Amiri, Beheshta, additional, Sindi, Suzanne S., additional, Weilhammer, Dina R., additional, Loots, Gabriela G., additional, and Hoyer, Katrina K., additional
- Published
- 2024
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11. Generalizing a mathematical model of prion aggregation allows strain coexistence and co-stability by including a novel misfolded species
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Lemarre, Paul, Pujo-Menjouet, Laurent, and Sindi, Suzanne S
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Biochemistry and Cell Biology ,Biological Sciences ,Rare Diseases ,Emerging Infectious Diseases ,Infectious Diseases ,Neurodegenerative ,Transmissible Spongiform Encephalopathy (TSE) ,Brain Disorders ,Neurosciences ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Animals ,Computational Biology ,Computer Simulation ,Humans ,Kinetics ,Mathematical Concepts ,Models ,Biological ,Models ,Molecular ,Phenotype ,Prion Diseases ,Prions ,Protein Aggregation ,Pathological ,Protein Conformation ,Protein Folding ,Protein Stability ,Proteostasis Deficiencies ,Coexistence ,Nucleated polymerization ,Protein aggregation ,Protein misfolding ,Strains ,Subunits ,Mathematical Sciences ,Bioinformatics ,Biological sciences ,Mathematical sciences - Abstract
Prions are proteins capable of adopting misfolded conformations and transmitting these conformations to other normally folded proteins. Prions are most commonly known for causing fatal neurodegenerative diseases in mammals but are also associated with several harmless phenotypes in yeast. A distinct feature of prion propagation is the existence of different phenotypical variants, called strains. It is widely accepted that these strains correspond to different conformational states of the protein, but the mechanisms driving their interactions remain poorly understood. This study uses mathematical modeling to provide insight into this problem. We show that the classical model of prion dynamics allows at most one conformational strain to stably propagate. In order to conform to biological observations of strain coexistence and co-stability, we develop an extension of the classical model by introducing a novel prion species consistent with biological studies. Qualitative analysis of this model reveals a new variety of behavior. Indeed, it allows for stable coexistence of different strains in a wide parameter range, and it also introduces intricate initial condition dependency. These new behaviors are consistent with experimental observations of prions in both mammals and yeast. As such, our model provides a valuable tool for investigating the underlying mechanisms of prion propagation and the link between prion strains and strain specific phenotypes. The consideration of a novel prion species brings a change in perspective on prion biology and we use our model to generate hypotheses about prion infectivity.
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- 2019
12. Mathematical Modeling for Women’s Health
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Ford Versypt, Ashlee N., Segal, Rebecca A., and Sindi, Suzanne S.
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Dynamical Systems ,Parameter estimation ,Differential equations ,Optimization ,Data science ,thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAX Computational biology / bioinformatics ,thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling ,thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBJ Maths for engineers - Abstract
The purpose of this work is to focus mathematical modeling on issues affecting women’s health. Working in six collaborative teams, researchers developed new mathematical models to address questions in a range of application areas. Topics include HIV, oral contraceptives, blood clotting, breast cancer, neonatal respiration, and outbreak forecasting. The work is the result of newly formed collaborative groups begun during the Collaborative Workshop for Women in Mathematical Biology hosted by the Institute of Mathematics and its Applications and UnitedHealth Group Optum in June 2022. This is an open access book.
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- 2024
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13. Multiple aspects of amyloid dynamics in vivo integrate to establish prion variant dominance in yeast.
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Norton, Jennifer, Seah, Nicole, Santiago, Fabian, Sindi, Suzanne S., and Serio, Tricia R.
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PROTEIN conformation ,PROTEIN-protein interactions ,AMYLOID ,ZYGOTES ,SOCIAL dominance - Abstract
Prion variants are self-perpetuating conformers of a single protein that assemble into amyloid fibers and confer unique phenotypic states. Multiple prion variants can arise, particularly in response to changing environments, and interact within an organism. These interactions are often competitive, with one variant establishing phenotypic dominance over the others. This dominance has been linked to the competition for non-prion state protein, which must be converted to the prion state via a nucleated polymerization mechanism. However, the intrinsic rates of conversion, determined by the conformation of the variant, cannot explain prion variant dominance, suggesting a more complex interaction. Using the yeast prion system [PSI
+ ], we have determined the mechanism of dominance of the [PSI+ ]Strong variant over the [PSI+ ]Weak variant in vivo. When mixed by mating, phenotypic dominance is established in zygotes, but the two variants persist and co-exist in the lineage descended from this cell. [PSI+ ]Strong propagons, the heritable unit, are amplified at the expense of [PSI+ ]Weak propagons, through the efficient conversion of soluble Sup35 protein, as revealed by fluorescence photobleaching experiments employing variantspecific mutants of Sup35. This competition, however, is highly sensitive to the fragmentation of [PSI+ ]Strong amyloid fibers, with even transient inhibition of the fragmentation catalyst Hsp104 promoting amplification of [PSI+ ]Weak propagons. Reducing the number of [PSI+]Strong propagons prior to mating, similarly promotes [PSI+ ]Weak amplification and conversion of soluble Sup35, indicating that template number and conversion efficiency combine to determine dominance. Thus, prion variant dominance is not an absolute hierarchy but rather an outcome arising from the dynamic interplay between unique protein conformations and their interactions with distinct cellular proteostatic niches. [ABSTRACT FROM AUTHOR]- Published
- 2024
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14. CD8 Follicular T Cells Promote B Cell Antibody Class Switch in Autoimmune Disease
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Valentine, Kristen M, Davini, Dan, Lawrence, Travis J, Mullins, Genevieve N, Manansala, Miguel, Al-Kuhlani, Mufadhal, Pinney, James M, Davis, Jason K, Beaudin, Anna E, Sindi, Suzanne S, Gravano, David M, and Hoyer, Katrina K
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Autoimmune Disease ,2.1 Biological and endogenous factors ,Aetiology ,Inflammatory and immune system ,Anemia ,Hemolytic ,Autoimmune ,Animals ,Autoimmunity ,B-Lymphocytes ,CD8-Positive T-Lymphocytes ,Cell Differentiation ,Erythrocytes ,Female ,Immunoglobulin Class Switching ,Interleukin-2 ,Interleukins ,Male ,Mice ,Mice ,Inbred BALB C ,Mice ,Knockout ,Proto-Oncogene Proteins c-bcl-6 ,Receptors ,CXCR5 ,T-Lymphocytes ,Helper-Inducer ,Immunology - Abstract
CD8 T cells can play both a protective and pathogenic role in inflammation and autoimmune development. Recent studies have highlighted the ability of CD8 T cells to function as T follicular helper (Tfh) cells in the germinal center in the context of infection. However, whether this phenomenon occurs in autoimmunity and contributes to autoimmune pathogenesis is largely unexplored. In this study, we show that CD8 T cells acquire a CD4 Tfh profile in the absence of functional regulatory T cells in both the IL-2-deficient and scurfy mouse models. Depletion of CD8 T cells mitigates autoimmune pathogenesis in IL-2-deficient mice. CD8 T cells express the B cell follicle-localizing chemokine receptor CXCR5, a principal Tfh transcription factor Bcl6, and the Tfh effector cytokine IL-21. CD8 T cells localize to the B cell follicle, express B cell costimulatory proteins, and promote B cell differentiation and Ab isotype class switching. These data reveal a novel contribution of autoreactive CD8 T cells to autoimmune disease, in part, through CD4 follicular-like differentiation and functionality.
- Published
- 2018
15. A dominant-negative mutant inhibits multiple prion variants through a common mechanism.
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Pei, Fen, DiSalvo, Susanne, Sindi, Suzanne S, and Serio, Tricia R
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Saccharomyces cerevisiae ,Amyloid ,Saccharomyces cerevisiae Proteins ,Molecular Chaperones ,Prions ,Mutation ,Genetic Variation ,Prion Proteins ,Genetics ,Developmental Biology - Abstract
Prions adopt alternative, self-replicating protein conformations and thereby determine novel phenotypes that are often irreversible. Nevertheless, dominant-negative prion mutants can revert phenotypes associated with some conformations. These observations suggest that, while intervention is possible, distinct inhibitors must be developed to overcome the conformational plasticity of prions. To understand the basis of this specificity, we determined the impact of the G58D mutant of the Sup35 prion on three of its conformational variants, which form amyloids in S. cerevisiae. G58D had been previously proposed to have unique effects on these variants, but our studies suggest a common mechanism. All variants, including those reported to be resistant, are inhibited by G58D but at distinct doses. G58D lowers the kinetic stability of the associated amyloid, enhancing its fragmentation by molecular chaperones, promoting Sup35 resolubilization, and leading to amyloid clearance particularly in daughter cells. Reducing the availability or activity of the chaperone Hsp104, even transiently, reverses curing. Thus, the specificity of inhibition is determined by the sensitivity of variants to the mutant dosage rather than mode of action, challenging the view that a unique inhibitor must be developed to combat each variant.
- Published
- 2017
16. A mathematical model of coagulation under flow identifies factor V as a modifier of thrombin generation in hemophilia A
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Link, Kathryn G., Stobb, Michael T., Sorrells, Matthew G., Bortot, Maria, Ruegg, Katherine, Manco‐Johnson, Marilyn J., Di Paola, Jorge A., Sindi, Suzanne S., Fogelson, Aaron L., Leiderman, Karin, and Neeves, Keith B.
- Published
- 2020
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17. A mathematical model of the dynamics of prion aggregates with chaperone-mediated fragmentation
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Davis, Jason K and Sindi, Suzanne S
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Biochemistry and Cell Biology ,Biological Sciences ,Rare Diseases ,Emerging Infectious Diseases ,Brain Disorders ,Transmissible Spongiform Encephalopathy (TSE) ,Infectious Diseases ,Neurodegenerative ,Neurological ,Animals ,Heat-Shock Proteins ,Humans ,Kinetics ,Mathematical Concepts ,Models ,Biological ,Models ,Molecular ,Molecular Chaperones ,Peptide Termination Factors ,Prions ,Protein Aggregates ,Protein Aggregation ,Pathological ,Protein Folding ,Saccharomyces cerevisiae Proteins ,Nucleated polymerization ,Protein aggregation ,Protein misfolding ,Yeast ,Mathematical Sciences ,Bioinformatics ,Biological sciences ,Mathematical sciences - Abstract
Prions are proteins most commonly associated with fatal neurodegenerative diseases in mammals but are also responsible for a number of harmless heritable phenotypes in yeast. These states arise when a misfolded form of a protein appears and, rather than be removed by cellular quality control mechanisms, persists. The misfolded prion protein forms aggregates and is capable of converting normally folded protein to the misfolded state through direct interaction between the two forms. The dominant mathematical model for prion aggregate dynamics has been the nucleated polymerization model (NPM) which considers the dynamics of only the normal protein and the aggregates. However, for yeast prions the molecular chaperone Hsp104 is essential for prion propagation. Further, although mammals do not express Hsp104, experimental assays have shown Hsp104 also interacts with mammalian prion aggregates. In this study, we generalize the NPM to account for molecular chaperones and develop what we call the enzyme-limited nucleated polymerization model (ELNPM). We discuss existence, uniqueness and stability of solutions to our model and demonstrate that the NPM represents a quasi-steady-state reduction of our model. We validate the ELNPM by demonstrating agreement with experimental results on the yeast prion PSI(+) that could not be supported by the NPM. Finally, we demonstrate that, in contrast to the NPM, the ELNPM permits the coexistence of multiple prion strains.
- Published
- 2016
18. A study in nucleated polymerization models of protein aggregation
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Davis, Jason K and Sindi, Suzanne S
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Applied Mathematics ,Pure Mathematics ,Mathematical Sciences ,Alzheimer's Disease ,Infectious Diseases ,Aging ,Acquired Cognitive Impairment ,Neurodegenerative ,Neurosciences ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Brain Disorders ,Dementia ,Neurological ,Difference equation ,Generating function ,Prions ,Protein aggregates ,Nucleated polymerization ,difference equation ,generating function ,nucleated polymerization ,prions ,protein aggregates ,Applied mathematics ,Pure mathematics - Abstract
The nucleated polymerization model is a mathematical framework that has been applied to aggregation and fragmentation processes in both the discrete and continuous setting. In particular, this model has been the canonical framework for analyzing the dynamics of protein aggregates arising in prion and amyloid diseases such as as Alzheimer's and Parkinson's disease. We present an explicit steady-state solution to the aggregate size distribution governed by the discrete nucleated polymerization equations. Steady-state solutions have been previously obtained under the assumption of continuous aggregate sizes; however, the discrete solution allows for direct computation and parameter inference, as well as facilitates estimates on the accuracy of the continuous approximation.
- Published
- 2015
19. Amyloid-associated activity contributes to the severity and toxicity of a prion phenotype.
- Author
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Pezza, John A, Villali, Janice, Sindi, Suzanne S, and Serio, Tricia R
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Saccharomyces cerevisiae ,Amyloid ,Saccharomyces cerevisiae Proteins ,Prions ,Protein Folding - Abstract
The self-assembly of alternative conformations of normal proteins into amyloid aggregates has been implicated in both the acquisition of new functions and in the appearance and progression of disease. However, while these amyloidogenic pathways are linked to the emergence of new phenotypes, numerous studies have uncoupled the accumulation of aggregates from their biological consequences, revealing currently underappreciated complexity in the determination of these traits. Here, to explore the molecular basis of protein-only phenotypes, we focused on the Saccharomyces cerevisiae Sup35/[PSI(+)] prion, which confers a translation termination defect and expression level-dependent toxicity in its amyloid form. Our studies reveal that aggregated Sup35 retains its normal function as a translation release factor. However, fluctuations in the composition and size of these complexes specifically alter the level of this aggregate-associated activity and thereby the severity and toxicity of the amyloid state. Thus, amyloid heterogeneity is a crucial contributor to protein-only phenotypes.
- Published
- 2014
20. Computationally Driven Discovery in Coagulation
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Link, Kathryn G., Stobb, Michael T., Monroe, Dougald M., Fogelson, Aaron L., Neeves, Keith B., Sindi, Suzanne S., and Leiderman, Karin
- Published
- 2020
- Full Text
- View/download PDF
21. Boosting Single-Cell RNA Sequencing Analysis with Simple Neural Attention
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Davalos, Oscar A., Heydari, A. Ali, Fertig, Elana J., Sindi, Suzanne S., and Hoyer, Katrina K.
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Article - Abstract
A limitation of current deep learning (DL) approaches for single-cell RNA sequencing (scRNAseq) analysis is the lack of interpretability. Moreover, existing pipelines are designed and trained for specific tasks used disjointly for different stages of analysis. We present scANNA, a novel interpretable DL model for scR-NAseq studies that leverages neural attention to learn gene associations. After training, the learned gene importance (interpretability) is used to perform downstream analyses (e.g., global marker selection and cell-type classification) without retraining. ScANNA’s performance is comparable to or better than state-of-the-art methods designed and trained for specific standard scRNAseq analyses even though scANNA was not trained for these tasks explicitly. ScANNA enables researchers to discover meaningful results without extensive prior knowledge or training separate task-specific models, saving time and enhancing scRNAseq analyses.
- Published
- 2023
22. On analytical and numerical approaches to division and label structured population models
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Banks, H.T., Flores, Kevin B., and Sindi, Suzanne S.
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- 2016
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23. Deep learning in spatial transcriptomics: Learning from the next next-generation sequencing
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Heydari, A. Ali, primary and Sindi, Suzanne S., additional
- Published
- 2023
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24. Code, datasets, and results for the paper 'Inferring gene regulatory networks using transcriptional profiles as dynamical attractors'
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Ruihao Li, Rozum, Jordan C., Quail, Morgan M., Qasim, Mohammad N., Sindi, Suzanne S., Nobile, Clarissa J., Reka Albert, and Hernday, Aaron D.
- Abstract
This repository contains the supplemental materials for the study: "Inferring gene regulatory networks using transcriptional profiles as dynamical attractors". The supplemental materials consist of (1) the code of our evolutionary algorithm, (2) the datasets we used in the study,(3) the raw results of the GRN inferences, and (4) the mata spreadsheet that summarizes the GRN inference results.
- Published
- 2023
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25. A study in nucleated polymerization models of protein aggregation
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Davis, Jason K. and Sindi, Suzanne S.
- Published
- 2015
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26. ACTIVA: realistic single-cell RNA-seq generation with automatic cell-type identification using introspective variational autoencoders
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Heydari, A Ali, primary, Davalos, Oscar A, additional, Zhao, Lihong, additional, Hoyer, Katrina K, additional, and Sindi, Suzanne S, additional
- Published
- 2022
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27. A Size Threshold Limits Prion Transmission and Establishes Phenotypic Diversity
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Derdowski, Aaron, Sindi, Suzanne S., Klaips, Courtney L., DiSalvo, Susanne, and Serio, Tricia R.
- Published
- 2010
28. A field guide to cultivating computational biology
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Way, Gregory P., primary, Greene, Casey S., additional, Carninci, Piero, additional, Carvalho, Benilton S., additional, de Hoon, Michiel, additional, Finley, Stacey D., additional, Gosline, Sara J. C., additional, Lȇ Cao, Kim-Anh, additional, Lee, Jerry S. H., additional, Marchionni, Luigi, additional, Robine, Nicolas, additional, Sindi, Suzanne S., additional, Theis, Fabian J., additional, Yang, Jean Y. H., additional, Carpenter, Anne E., additional, and Fertig, Elana J., additional
- Published
- 2021
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29. A unifying model for the propagation of prion proteins in yeast brings insight into the [PSI+] prion
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Lemarre, Paul, primary, Pujo-Menjouet, Laurent, additional, and Sindi, Suzanne S., additional
- Published
- 2020
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30. How Emergent Social Patterns in Allogrooming Combat Parasitic Infections
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Wilson, Shelby N., primary, Sindi, Suzanne S., additional, Brooks, Heather Z., additional, Hohn, Maryann E., additional, Price, Candice R., additional, Radunskaya, Ami E., additional, Williams, Nakeya D., additional, and Fefferman, Nina H., additional
- Published
- 2020
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31. Identification of polymorphic inversions from genotypes
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Cáceres Alejandro, Sindi Suzanne S, Raphael Benjamin J, Cáceres Mario, and González Juan R
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Polymorphic inversions are a source of genetic variability with a direct impact on recombination frequencies. Given the difficulty of their experimental study, computational methods have been developed to infer their existence in a large number of individuals using genome-wide data of nucleotide variation. Methods based on haplotype tagging of known inversions attempt to classify individuals as having a normal or inverted allele. Other methods that measure differences between linkage disequilibrium attempt to identify regions with inversions but unable to classify subjects accurately, an essential requirement for association studies. Results We present a novel method to both identify polymorphic inversions from genome-wide genotype data and classify individuals as containing a normal or inverted allele. Our method, a generalization of a published method for haplotype data 1, utilizes linkage between groups of SNPs to partition a set of individuals into normal and inverted subpopulations. We employ a sliding window scan to identify regions likely to have an inversion, and accumulation of evidence from neighboring SNPs is used to accurately determine the inversion status of each subject. Further, our approach detects inversions directly from genotype data, thus increasing its usability to current genome-wide association studies (GWAS). Conclusions We demonstrate the accuracy of our method to detect inversions and classify individuals on principled-simulated genotypes, produced by the evolution of an inversion event within a coalescent model 2. We applied our method to real genotype data from HapMap Phase III to characterize the inversion status of two known inversions within the regions 17q21 and 8p23 across 1184 individuals. Finally, we scan the full genomes of the European Origin (CEU) and Yoruba (YRI) HapMap samples. We find population-based evidence for 9 out of 15 well-established autosomic inversions, and for 52 regions previously predicted by independent experimental methods in ten (9+1) individuals 34. We provide efficient implementations of both genotype and haplotype methods as a unified R package inveRsion.
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- 2012
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32. Computationally Driven Discovery in Coagulation.
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Link, Kathryn G., Stobb, Michael T., Monroe, Dougald M., Fogelson, Aaron L., Neeves, Keith B., Sindi, Suzanne S., and Leiderman, Karin
- Published
- 2021
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33. Mathematical Modeling of Prion Disease
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Sindi, Suzanne S.
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Medical / Infectious Diseases - Abstract
The prion hypothesis, once a heretical violation of the central dogma of molecular biology, has become an accepted mechanism used to explain a host of progressive neurodegenerative diseases in mammals and heritable phenotypes in yeast. From the beginning, mathematical models have been an essential tool in studying prion and other protein misfolding/aggregation processes. In this work, we review some of the major mathematical studies that have contributed to our understanding of prion disease and discuss trends in current and future studies.
- Published
- 2017
34. MultiCellDS: a standard and a community for sharing multicellular data
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Friedman, Samuel H., Anderson, Alexander R. A., Bortz, David M., Fletcher, Alexander G., Frieboes, Hermann B., Ghaffarizadeh, Ahmadreza, Grimes, David Robert, Hawkins-Daarud, Andrea, Hoehme, Stefan, Juarez, Edwin F., Kesselman, Carl, Merks, Roeland M.H., Mumenthaler, Shannon M., Newton, Paul K., Norton, Kerri-Ann, Rawat, Rishi, Rockne, Russell C., Ruderman, Daniel, Scott, Jacob, Sindi, Suzanne S., Sparks, Jessica L., Swanson, Kristin, Agus, David B., and Macklin, Paul
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0303 health sciences ,Computer science ,business.industry ,Systems biology ,Data science ,Data Standard ,03 medical and health sciences ,Human health ,Multicellular organism ,0302 clinical medicine ,Software ,Multidisciplinary approach ,030220 oncology & carcinogenesis ,business ,030304 developmental biology - Abstract
Cell biology is increasingly focused on cellular heterogeneity and multicellular systems. To make the fullest use of experimental, clinical, and computational efforts, we need standardized data formats, community-curated “public data libraries”, and tools to combine and analyze shared data. To address these needs, our multidisciplinary community created MultiCellDS (MultiCellular Data Standard): an extensible standard, a library of digital cell lines and tissue snapshots, and support software. With the help of experimentalists, clinicians, modelers, and data and library scientists, we can grow this seed into a community-owned ecosystem of shared data and tools, to the benefit of basic science, engineering, and human health.
- Published
- 2016
35. A unifying model for the propagation of prion proteins in yeast brings insight into the [PSI+] prion.
- Author
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Lemarre, Paul, Pujo-Menjouet, Laurent, and Sindi, Suzanne S.
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PRIONS ,IMPULSIVE differential equations ,CHEMICAL processes ,YEAST ,GUANIDINIUM chlorides - Abstract
The use of yeast systems to study the propagation of prions and amyloids has emerged as a crucial aspect of the global endeavor to understand those mechanisms. Yeast prion systems are intrinsically multi-scale: the molecular chemical processes are indeed coupled to the cellular processes of cell growth and division to influence phenotypical traits, observable at the scale of colonies. We introduce a novel modeling framework to tackle this difficulty using impulsive differential equations. We apply this approach to the [PSI
+ ] yeast prion, which is associated with the misconformation and aggregation of Sup35. We build a model that reproduces and unifies previously conflicting experimental observations on [PSI+ ] and thus sheds light onto characteristics of the intracellular molecular processes driving aggregate replication. In particular our model uncovers a kinetic barrier for aggregate replication at low densities, meaning the change between prion or prion-free phenotype is a bi-stable transition. This result is based on the study of prion curing experiments, as well as the phenomenon of colony sectoring, a phenotype which is often ignored in experimental assays and has never been modeled. Furthermore, our results provide further insight into the effect of guanidine hydrochloride (GdnHCl) on Sup35 aggregates. To qualitatively reproduce the GdnHCl curing experiment, aggregate replication must not be completely inhibited, which suggests the existence of a mechanism different than Hsp104-mediated fragmentation. Those results are promising for further development of the [PSI+ ] model, but also for extending the use of this novel framework to other yeast prion or amyloid systems. Author summary: In the study of yeast prions, mathematical modeling is a powerful tool, in particular when it comes to facing the difficulties of multi-scale systems. In this study, we introduce a mathematical framework for investigating this problem in a unifying way. We focus on the yeast prion [PSI+ ] and present a simple molecular scheme for prion replication and a model of yeast budding. In order to qualitatively reproduce experiments, we need to introduce a non-linear mechanism in the molecular rates. This transforms the intracellular system into a bi-stable switch and allows for curing to occur, which is a crucial phenomenon for the study of yeast prions. To the best of our knowledge, no model in the literature includes such a mechanism, at least not explicitly. We also describe the GdnHCl curing experiment, and the propagon counting procedure. Reproducing this result requires challenging hypotheses that are commonly accepted, and our interpretation gives a new perspective on the concept of propagon. This study may be considered as a good example of how mathematical modeling can bring valuable insight into biological concepts and observations. [ABSTRACT FROM AUTHOR]- Published
- 2020
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36. A local and global sensitivity analysis of a mathematical model of coagulation and platelet deposition under flow
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Link, Kathryn G., primary, Stobb, Michael T., additional, Di Paola, Jorge, additional, Neeves, Keith B., additional, Fogelson, Aaron L., additional, Sindi, Suzanne S., additional, and Leiderman, Karin, additional
- Published
- 2018
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37. Distinct Prion Domain Sequences Ensure Efficient Amyloid Propagation by Promoting Chaperone Binding or Processing In Vivo
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Langlois, Christine R., primary, Pei, Fen, additional, Sindi, Suzanne S., additional, and Serio, Tricia R., additional
- Published
- 2016
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38. Identification and Frequency Estimation of Inversion Polymorphisms from Haplotype Data
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Sindi, Suzanne S., primary and Raphael, Benjamin J., additional
- Published
- 2010
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39. An integrative probabilistic model for identification of structural variation in sequencing data.
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Sindi, Suzanne S., önal, Selim, Peng, Luke C., Hsin-Ta Wu, and Raphael, Benjamin J.
- Published
- 2012
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40. Deconstructing the Contributions of Heterogeneity to Combination Treatment of Hormone-Sensitive Breast Cancer
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Linn, Samantha, Moore-Ott, Jenna A., Shuttleworth, Robyn, Zhang, Wenjing, Craig, Morgan, Jenner, Adrianne L., Spirn, Daniel, Series Editor, Ford Versypt, Ashlee N., editor, Segal, Rebecca A., editor, and Sindi, Suzanne S., editor
- Published
- 2024
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41. Extended-Release Pre-exposure Prophylaxis and Drug-Resistant HIV
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Ma, Yanping, Kang, Yeona, Davenport, Angelica, Aduamah, Jennifer Mawunyo, Link, Kathryn, Gurski, Katharine, Spirn, Daniel, Series Editor, Ford Versypt, Ashlee N., editor, Segal, Rebecca A., editor, and Sindi, Suzanne S., editor
- Published
- 2024
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42. Estimation of Time-Dependent Transmission Rate for COVID-19 SVIRD Model Using Predictor–Corrector Algorithm
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Luo, Ruiyan, Herrera-Reyes, Alejandra D., Kim, Yena, Rogowski, Susan, White, Diana, Smirnova, Alexandra, Spirn, Daniel, Series Editor, Ford Versypt, Ashlee N., editor, Segal, Rebecca A., editor, and Sindi, Suzanne S., editor
- Published
- 2024
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43. Towards a Mathematical Understanding of Ventilator-Induced Lung Injury in Preterm Rat Pups
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Luke, Rayanne A., Kelly, Gess, Stoner, Melissa, O’Brien, Jordana Esplin, Lubkin, Sharon R., Fix, Laura Ellwein, Spirn, Daniel, Series Editor, Ford Versypt, Ashlee N., editor, Segal, Rebecca A., editor, and Sindi, Suzanne S., editor
- Published
- 2024
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44. A Survey of Mathematical Modeling of Hormonal Contraception and the Menstrual Cycle
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Zhao, Lihong, Kim, Ruby, Oremland, Lucy S., Chowkwale, Mukti, Pillis, Lisette G. de, Brooks, Heather Z., Spirn, Daniel, Series Editor, Ford Versypt, Ashlee N., editor, Segal, Rebecca A., editor, and Sindi, Suzanne S., editor
- Published
- 2024
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45. MultiCellDS : a community-developed standard for curating microenvironment-dependent multicellular data
- Author
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Friedman, Samuel H., Anderson, Alexander R. A., Bortz, David M., Fletcher, Alexander G., Frieboes, Hermann B., Ghaffarizadeh, Ahmadreza, Grimes, David Robert, Hawkins-Daarud, Andrea, Hoehme, Stefan, Juarez, Edwin F., Kesselman, Carl, Merks, Roeland M.H., Mumenthaler, Shannon M., Newton, Paul K., Norton, Kerri-Ann, Rawat, Rishi, Rockne, Russell C., Ruderman, Daniel, Scott, Jacob, Sindi, Suzanne S., Sparks, Jessica L., Swanson, Kristin, Agus, David B., and Macklin, Paul
- Subjects
Metadata ,Data Standard ,World Wide Web ,Multicellular organism ,Data curation ,Cell culture ,Computer science ,Systems biology ,Context (language use) ,Data science ,Discoverability - Abstract
Exchanging and understanding scientific data and their context represents a significant barrier to advancing research, especially with respect to information siloing. Maintaining information provenance and providing data curation and quality control help overcome common concerns and barriers to the effective sharing of scientific data. To address these problems in and the unique challenges of multicellular systems, we assembled a panel composed of investigators from several disciplines to create the MultiCellular Data Standard (MultiCellDS) with a use-case driven development process. The standard includes (1) digital cell lines, which are analogous to traditional biological cell lines, to record metadata, cellular microenvironment, and cellular phenotype variables of a biological cell line, (2) digital snapshots to consistently record simulation, experimental, and clinical data for multicellular systems, and (3) collections that can logically group digital cell lines and snapshots. We have created a MultiCellular DataBase (MultiCellDB) to store digital snapshots and the 200+ digital cell lines we have generated. MultiCellDS, by having a fixed standard, enables discoverability, extensibility, maintainability, searchability, and sustainability of data, creating biological applicability and clinical utility that permits us to identify upcoming challenges to uplift biology and strategies and therapies for improving human health.
46. Host tracheal and intestinal microbiomes inhibit Coccidioides growth in vitro .
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Tejeda-Garibay S, Zhao L, Hum NR, Pimentel M, Diep AL, Amiri B, Sindi SS, Weilhammer DR, Loots GG, and Hoyer KK
- Abstract
Coccidioidomycosis, also known as Valley fever, is a disease caused by the fungal pathogen Coccidioides . Unfortunately, patients are often misdiagnosed with bacterial pneumonia leading to inappropriate antibiotic treatment. Soil bacteria B. subtilis -like species exhibits antagonistic properties against Coccidioides in vitro ; however, the antagonistic capabilities of host microbiota against Coccidioides are unexplored. We sought to examine the potential of the tracheal and intestinal microbiomes to inhibit the growth of Coccidioides in vitro . We hypothesized that an uninterrupted lawn of microbiota obtained from antibiotic-free mice would inhibit the growth of Coccidioides while partial in vitro depletion through antibiotic disk diffusion assays would allow a niche for fungal growth. We observed that the microbiota grown on 2xGYE (GYE) and CNA w/ 5% sheep's blood agar (5%SB-CNA) inhibited the growth of Coccidioides , but that grown on chocolate agar does not. Partial depletion of the microbiota through antibiotic disk diffusion revealed that microbiota depletion leads to diminished inhibition and comparable growth of Coccidioides growth to controls. To characterize the bacteria grown and narrow down potential candidates contributing to the inhibition of Coccidioides , 16s rRNA sequencing of tracheal and intestinal agar cultures and murine lung extracts was performed. The identity of host bacteria that may be responsible for this inhibition was revealed. The results of this study demonstrate the potential of the host microbiota to inhibit the growth of Coccidioides in vitro and suggest that an altered microbiome through antibiotic treatment could negatively impact effective fungal clearance and allow a niche for fungal growth in vivo .
- Published
- 2023
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47. AddTag, a two-step approach with supporting software package that facilitates CRISPR/Cas-mediated precision genome editing.
- Author
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Seher TD, Nguyen N, Ramos D, Bapat P, Nobile CJ, Sindi SS, and Hernday AD
- Subjects
- Genetic Engineering, Genomics, Software, CRISPR-Cas Systems, Gene Editing
- Abstract
CRISPR/Cas-induced genome editing is a powerful tool for genetic engineering, however, targeting constraints limit which loci are editable with this method. Since the length of a DNA sequence impacts the likelihood it overlaps a unique target site, precision editing of small genomic features with CRISPR/Cas remains an obstacle. We introduce a two-step genome editing strategy that virtually eliminates CRISPR/Cas targeting constraints and facilitates precision genome editing of elements as short as a single base-pair at virtually any locus in any organism that supports CRISPR/Cas-induced genome editing. Our two-step approach first replaces the locus of interest with an "AddTag" sequence, which is subsequently replaced with any engineered sequence, and thus circumvents the need for direct overlap with a unique CRISPR/Cas target site. In this study, we demonstrate the feasibility of our approach by editing transcription factor binding sites within Candida albicans that could not be targeted directly using the traditional gene-editing approach. We also demonstrate the utility of the AddTag approach for combinatorial genome editing and gene complementation analysis, and we present a software package that automates the design of AddTag editing., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.)
- Published
- 2021
- Full Text
- View/download PDF
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