Applied and Environmental Microbiology, Nov 1, 2018
Salmonella enterica is represented by Ͼ2,600 serovars that can differ in routes of transmission, ... more Salmonella enterica is represented by Ͼ2,600 serovars that can differ in routes of transmission, host colonization, and in resistance to antimicrobials. S. enterica is the leading bacterial cause of foodborne illness in the United States, with well-established detection methodology. Current surveillance protocols rely on the characterization of a few colonies to represent an entire sample; thus, minority serovars remain undetected. Salmonella contains two CRISPR loci, CRISPR1 and CRISPR2, and the spacer contents of these can be considered serovar specific. We exploited this property to develop an amplicon-based and multiplexed sequencing approach, CRISPR-SeroSeq (serotyping by sequencing of the CRISPR loci), to identify multiple serovars present in a single sample. Using mixed genomic DNA from two Salmonella serovars, we were able to confidently detect a serovar that constituted 0.01% of the sample. Poultry is a major reservoir of Salmonella spp., including serovars that are frequently associated with human illness, as well as those that are not. Numerous studies have examined the prevalence and diversity of Salmonella spp. in poultry, though these studies were limited to culture-based approaches and therefore only identified abundant serovars. CRISPR-SeroSeq was used to investigate samples from broiler houses and a processing facility. Ninety-one percent of samples harbored multiple serovars, and there was one sample in which four different serovars were detected. In another sample, reads for the minority serovar comprised 0.003% of the total number of Salmonella spacer reads. The most abundant serovars identified were Salmonella enterica serovars Montevideo, Kentucky, Enteritidis, and Typhimurium. CRISPR-SeroSeq also differentiated between multiple strains of some serovars. This high resolution of serovar populations has the potential to be utilized as a powerful tool in the surveillance of Salmonella species. IMPORTANCE Salmonella enterica is the leading bacterial cause of foodborne illness in the United States and is represented by over 2,600 distinct serovars. Some of these serovars are pathogenic in humans, while others are not. Current surveillance for this pathogen is limited by the detection of only the most abundant serovars, due to the culture-based approaches that are used. Thus, pathogenic serovars that are present in a minority remain undetected. By exploiting serovar-specific differences in the CRISPR arrays of Salmonella spp., we have developed a highthroughput sequencing tool to be able to identify multiple serovars in a single sample and tested this in multiple poultry samples. This novel approach allows differences in the dynamics of individual Salmonella serovars to be measured and can have a significant impact on understanding the ecology of this pathogen with respect to zoonotic risk and public health.
bioRxiv (Cold Spring Harbor Laboratory), Jul 19, 2022
Reproducibility is science has plagued efforts to understand biology at both basic and biomedical... more Reproducibility is science has plagued efforts to understand biology at both basic and biomedical and preclinical research levels. Poor experimental design and execution can result in datasets that are improperly powered to produce rigorous and reproducible results. In order to help biologists better model their data, here we present a statistical package called RMeDPower in R, which is a complete package of statistical tools that allow a scientist to understand the effect size and variance contribution of a set of variables one has within a dataset to a given response. RMeDPower can estimate the effect size of variables within an experiment based on an initial pilot dataset. In this way, RMeDPower can inform the user how to predict the scope, dimension and size of biological data needed for a particular experimental design. RMeDPower employs a generalized linear mixed model (LMM)-based power analysis, specifically targeting cell culture-based biological experimental designs. This package simulates experiments based on user-provided experimental design related variables, such as experiments, plates, and cell lines as random effects variables. This package not only allows us to use pilot data to estimate variance components for power simulation, it also accepts a set of variance components, which is an estimation of variance of the random effects linked to experimental variables and transformed into Intra-class Correlation Coefficients (ICC), as input which is precalculated from different data sets. The latter case is suitable when pilot data has an insufficient number of replications of experimental variables to directly estimate associated variance components. RMeDPower is a powerful package that any scientist or cell biologist can use to determine if a dataset is adequately powered for each experiment and then model accordingly.
The clinical presentation of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disea... more The clinical presentation of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disease, varies widely across patients, making it challenging to determine if potential therapeutics slow progression. We sought to determine whether there were common patterns of disease progression that could aid in the design and analysis of clinical trials. We developed an approach based on a mixture of Gaussian processes to identify clusters of patients sharing similar disease progression patterns, modeling their average trajectories and the variability in each cluster. We show that ALS progression is frequently nonlinear, with periods of stable disease preceded or followed by rapid decline. We also show that our approach can be extended to Alzheimer’s and Parkinson’s diseases. Our results advance the characterization of disease progression of ALS and provide a flexible modeling approach that can be applied to other progressive diseases.
Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iP... more Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical–molecular–biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlyin...
Applied and environmental microbiology, Jan 31, 2018
is represented by >2,600 serovars that can differ in routes of transmission, host colonization... more is represented by >2,600 serovars that can differ in routes of transmission, host colonization, and in resistance to antimicrobials. is the leading bacterial cause of foodborne illness in the United States with well-established detection methodology. Current surveillance protocols rely on characterization of a few colonies to represent an entire sample, thus minority serovars remain undetected. contains two CRISPR loci, CRISPR1 and CRISPR2, and the spacer content of these can be considered serovar specific. We exploited this property to develop an amplicon-based and multiplexed sequencing approach, CRISPR-SeroSeq, to identify multiple serovars present in a single sample. Using mixed genomic DNA from two serovars, we were able to confidently detect a serovar that constituted 0.01% of the sample.Poultry is a major reservoir for , including serovars that are frequently associated with human illness, as well as those that are not. Numerous studies have examined the prevalence and div...
Applied and Environmental Microbiology, Nov 1, 2018
Salmonella enterica is represented by Ͼ2,600 serovars that can differ in routes of transmission, ... more Salmonella enterica is represented by Ͼ2,600 serovars that can differ in routes of transmission, host colonization, and in resistance to antimicrobials. S. enterica is the leading bacterial cause of foodborne illness in the United States, with well-established detection methodology. Current surveillance protocols rely on the characterization of a few colonies to represent an entire sample; thus, minority serovars remain undetected. Salmonella contains two CRISPR loci, CRISPR1 and CRISPR2, and the spacer contents of these can be considered serovar specific. We exploited this property to develop an amplicon-based and multiplexed sequencing approach, CRISPR-SeroSeq (serotyping by sequencing of the CRISPR loci), to identify multiple serovars present in a single sample. Using mixed genomic DNA from two Salmonella serovars, we were able to confidently detect a serovar that constituted 0.01% of the sample. Poultry is a major reservoir of Salmonella spp., including serovars that are frequently associated with human illness, as well as those that are not. Numerous studies have examined the prevalence and diversity of Salmonella spp. in poultry, though these studies were limited to culture-based approaches and therefore only identified abundant serovars. CRISPR-SeroSeq was used to investigate samples from broiler houses and a processing facility. Ninety-one percent of samples harbored multiple serovars, and there was one sample in which four different serovars were detected. In another sample, reads for the minority serovar comprised 0.003% of the total number of Salmonella spacer reads. The most abundant serovars identified were Salmonella enterica serovars Montevideo, Kentucky, Enteritidis, and Typhimurium. CRISPR-SeroSeq also differentiated between multiple strains of some serovars. This high resolution of serovar populations has the potential to be utilized as a powerful tool in the surveillance of Salmonella species. IMPORTANCE Salmonella enterica is the leading bacterial cause of foodborne illness in the United States and is represented by over 2,600 distinct serovars. Some of these serovars are pathogenic in humans, while others are not. Current surveillance for this pathogen is limited by the detection of only the most abundant serovars, due to the culture-based approaches that are used. Thus, pathogenic serovars that are present in a minority remain undetected. By exploiting serovar-specific differences in the CRISPR arrays of Salmonella spp., we have developed a highthroughput sequencing tool to be able to identify multiple serovars in a single sample and tested this in multiple poultry samples. This novel approach allows differences in the dynamics of individual Salmonella serovars to be measured and can have a significant impact on understanding the ecology of this pathogen with respect to zoonotic risk and public health.
bioRxiv (Cold Spring Harbor Laboratory), Jul 19, 2022
Reproducibility is science has plagued efforts to understand biology at both basic and biomedical... more Reproducibility is science has plagued efforts to understand biology at both basic and biomedical and preclinical research levels. Poor experimental design and execution can result in datasets that are improperly powered to produce rigorous and reproducible results. In order to help biologists better model their data, here we present a statistical package called RMeDPower in R, which is a complete package of statistical tools that allow a scientist to understand the effect size and variance contribution of a set of variables one has within a dataset to a given response. RMeDPower can estimate the effect size of variables within an experiment based on an initial pilot dataset. In this way, RMeDPower can inform the user how to predict the scope, dimension and size of biological data needed for a particular experimental design. RMeDPower employs a generalized linear mixed model (LMM)-based power analysis, specifically targeting cell culture-based biological experimental designs. This package simulates experiments based on user-provided experimental design related variables, such as experiments, plates, and cell lines as random effects variables. This package not only allows us to use pilot data to estimate variance components for power simulation, it also accepts a set of variance components, which is an estimation of variance of the random effects linked to experimental variables and transformed into Intra-class Correlation Coefficients (ICC), as input which is precalculated from different data sets. The latter case is suitable when pilot data has an insufficient number of replications of experimental variables to directly estimate associated variance components. RMeDPower is a powerful package that any scientist or cell biologist can use to determine if a dataset is adequately powered for each experiment and then model accordingly.
The clinical presentation of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disea... more The clinical presentation of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disease, varies widely across patients, making it challenging to determine if potential therapeutics slow progression. We sought to determine whether there were common patterns of disease progression that could aid in the design and analysis of clinical trials. We developed an approach based on a mixture of Gaussian processes to identify clusters of patients sharing similar disease progression patterns, modeling their average trajectories and the variability in each cluster. We show that ALS progression is frequently nonlinear, with periods of stable disease preceded or followed by rapid decline. We also show that our approach can be extended to Alzheimer’s and Parkinson’s diseases. Our results advance the characterization of disease progression of ALS and provide a flexible modeling approach that can be applied to other progressive diseases.
Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iP... more Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical–molecular–biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlyin...
Applied and environmental microbiology, Jan 31, 2018
is represented by >2,600 serovars that can differ in routes of transmission, host colonization... more is represented by >2,600 serovars that can differ in routes of transmission, host colonization, and in resistance to antimicrobials. is the leading bacterial cause of foodborne illness in the United States with well-established detection methodology. Current surveillance protocols rely on characterization of a few colonies to represent an entire sample, thus minority serovars remain undetected. contains two CRISPR loci, CRISPR1 and CRISPR2, and the spacer content of these can be considered serovar specific. We exploited this property to develop an amplicon-based and multiplexed sequencing approach, CRISPR-SeroSeq, to identify multiple serovars present in a single sample. Using mixed genomic DNA from two serovars, we were able to confidently detect a serovar that constituted 0.01% of the sample.Poultry is a major reservoir for , including serovars that are frequently associated with human illness, as well as those that are not. Numerous studies have examined the prevalence and div...
Uploads
Papers by Naufa Amirani