Showing papers by "James B. Brown published in 2020"
TL;DR: In this paper, the authors identify globally distributed haplotypes from 15,789 SARS-CoV-2 genomes and model their success based on their duration, dispersal, and frequency in the host population.
Abstract: A mechanistic understanding of the spread of SARS-CoV-2 and diligent tracking of ongoing mutagenesis are of key importance to plan robust strategies for confining its transmission. Large numbers of available sequences and their dates of transmission provide an unprecedented opportunity to analyze evolutionary adaptation in novel ways. Addition of high-resolution structural information can reveal the functional basis of these processes at the molecular level. Integrated systems biology-directed analyses of these data layers afford valuable insights to build a global understanding of the COVID-19 pandemic. Here we identify globally distributed haplotypes from 15,789 SARS-CoV-2 genomes and model their success based on their duration, dispersal, and frequency in the host population. Our models identify mutations that are likely compensatory adaptive changes that allowed for rapid expansion of the virus. Functional predictions from structural analyses indicate that, contrary to previous reports, the Asp614Gly mutation in the spike glycoprotein (S) likely reduced transmission and the subsequent Pro323Leu mutation in the RNA-dependent RNA polymerase led to the precipitous spread of the virus. Our model also suggests that two mutations in the nsp13 helicase allowed for the adaptation of the virus to the Pacific Northwest of the USA. Finally, our explainable artificial intelligence algorithm identified a mutational hotspot in the sequence of S that also displays a signature of positive selection and may have implications for tissue or cell-specific expression of the virus. These results provide valuable insights for the development of drugs and surveillance strategies to combat the current and future pandemics.
52 citations
TL;DR: Advances toward tackling technological hurdles to solve multiple United Nations Sustainable Development Goals are reviewed and a vision to overcome gaps between research and policy is discussed.
31 citations
TL;DR: The effects of "pristine" and "aged" Ag NPs are systematically evaluated with different surface coatings on Daphnia magna over four generations, comparing continuous exposure versus parental only exposure to assess recovery potential for three generations.
Abstract: Engineered nanoparticles (NPs) undergo physical, chemical, and biological transformation after environmental release, resulting in different properties of the "aged" versus "pristine" forms. While many studies have investigated the ecotoxicological effects of silver (Ag) NPs, the majority focus on "pristine" Ag NPs in simple exposure media, rather than investigating realistic environmental exposure scenarios with transformed NPs. Here, the effects of "pristine" and "aged" Ag NPs are systematically evaluated with different surface coatings on Daphnia magna over four generations, comparing continuous exposure versus parental only exposure to assess recovery potential for three generations. Biological endpoints including survival, growth and reproduction and genetic effects associated with Ag NP exposure are investigated. Parental exposure to "pristine" Ag NPs has an inhibitory effect on reproduction, inducing expression of antioxidant stress related genes and reducing survival. Pristine Ag NPs also induce morphological changes including tail losses and lipid accumulation associated with aging phenotypes in the heart, abdomen, and abdominal claw. These effects are epigenetic remaining two generations post-maternal exposure (F2 and F3). Exposure to identical Ag NPs (same concentrations) aged for 6 months in environmentally realistic water containing natural organic matter shows considerably reduced toxicological effects in continuously exposed generations and to the recovery generations.
29 citations
TL;DR: A workshop brought together representatives from industry, academia and government to discuss how to improve the use of existing data, and to generate new NAMs data to derive better mechanistic understanding between humans and environmentally-relevant species, ultimately resulting in holistic chemical safety decisions.
27 citations
TL;DR: The epigenetic differences between male and female in Daphnia pulex are vast and dominated by changes that promote elevated gene expression in male Daphnian, and these changes relate to pathways that are physiologically relevant to the observed phenotypic differences.
Abstract: Daphnia species reproduce by cyclic parthenogenesis involving both sexual and asexual reproduction. The sex of the offspring is environmentally determined and mediated via endocrine signalling by the mother. Interestingly, male and female Daphnia can be genetically identical, yet display large differences in behaviour, morphology, lifespan and metabolic activity. Our goal was to integrate multiple omics datasets, including gene expression, splicing, histone modification and DNA methylation data generated from genetically identical female and male Daphnia pulex under controlled laboratory settings with the aim of achieving a better understanding of the underlying epigenetic factors that may contribute to the phenotypic differences observed between the two genders. In this study we demonstrate that gene expression level is positively correlated with increased DNA methylation, and histone H3 trimethylation at lysine 4 (H3K4me3) at predicted promoter regions. Conversely, elevated histone H3 trimethylation at lysine 27 (H3K27me3), distributed across the entire transcript length, is negatively correlated with gene expression level. Interestingly, male Daphnia are dominated with epigenetic modifications that globally promote elevated gene expression, while female Daphnia are dominated with epigenetic modifications that reduce gene expression globally. For examples, CpG methylation (positively correlated with gene expression level) is significantly higher in almost all differentially methylated sites in male compared to female Daphnia. Furthermore, H3K4me3 modifications are higher in male compared to female Daphnia in more than 3/4 of the differentially regulated promoters. On the other hand, H3K27me3 is higher in female compared to male Daphnia in more than 5/6 of differentially modified sites. However, both sexes demonstrate roughly equal number of genes that are up-regulated in one gender compared to the other sex. Since, gene expression analyses typically assume that most genes are expressed at equal level among samples and different conditions, and thus cannot detect global changes affecting most genes. The epigenetic differences between male and female in Daphnia pulex are vast and dominated by changes that promote elevated gene expression in male Daphnia. Furthermore, the differences observed in both gene expression changes and epigenetic modifications between the genders relate to pathways that are physiologically relevant to the observed phenotypic differences.
26 citations
TL;DR: In this paper, the authors apply a system biology approach to quantify the impact of glyphosate and its commercial formula, Roundup, on fitness, genome-wide transcription and gut microbiota, taking full advantage of clonal reproduction in Daphnia.
Abstract: Research around the weedkiller Roundup is among the most contentious of the twenty-first century. Scientists have provided inconclusive evidence that the weedkiller causes cancer and other life-threatening diseases, while industry-paid research reports that the weedkiller has no adverse effect on humans or animals. Much of the controversial evidence on Roundup is rooted in the approach used to determine safe use of chemicals, defined by outdated toxicity tests. We apply a system biology approach to the biomedical and ecological model species Daphnia to quantify the impact of glyphosate and of its commercial formula, Roundup, on fitness, genome-wide transcription and gut microbiota, taking full advantage of clonal reproduction in Daphnia. We then apply machine learning-based statistical analysis to identify and prioritize correlations between genome-wide transcriptional and microbiota changes. We demonstrate that chronic exposure to ecologically relevant concentrations of glyphosate and Roundup at the approved regulatory threshold for drinking water in the US induce embryonic developmental failure, induce significant DNA damage (genotoxicity), and interfere with signaling. Furthermore, chronic exposure to the weedkiller alters the gut microbiota functionality and composition interfering with carbon and fat metabolism, as well as homeostasis. Using the “Reactome,” we identify conserved pathways across the Tree of Life, which are potential targets for Roundup in other species, including liver metabolism, inflammation pathways, and collagen degradation, responsible for the repair of wounds and tissue remodeling. Our results show that chronic exposure to concentrations of Roundup and glyphosate at the approved regulatory threshold for drinking water causes embryonic development failure and alteration of key metabolic functions via direct effect on the host molecular processes and indirect effect on the gut microbiota. The ecological model species Daphnia occupies a central position in the food web of aquatic ecosystems, being the preferred food of small vertebrates and invertebrates as well as a grazer of algae and bacteria. The impact of the weedkiller on this keystone species has cascading effects on aquatic food webs, affecting their ability to deliver critical ecosystem services.
24 citations
TL;DR: Wainwright et al. as discussed by the authors found that the intensity of early summer (the "foresummer" period from May to June) drought conditions appears to impose critical controls on peak ecosystem productivity.
Abstract: Author(s): Wainwright, HM; Steefel, C; Trutner, SD; Henderson, AN; Nikolopoulos, EI; Wilmer, CF; Chadwick, KD; Falco, N; Schaettle, KB; Brown, JB; Steltzer, H; Williams, KH; Hubbard, SS; Enquist, BJ | Abstract: Long-term plot-scale studies have found water limitation to be a key factor driving ecosystem productivity in the Rocky Mountains. Specifically, the intensity of early summer (the 'foresummer' period from May to June) drought conditions appears to impose critical controls on peak ecosystem productivity. This study aims to (1) assess the importance of early snowmelt and foresummer drought in controlling peak plant productivity, based on the historical Landsat normalized-difference vegetation index (NDVI) and climate data; (2) map the spatial heterogeneity of foresummer drought sensitivity; and (3) identify the environmental controls (e.g. geomorphology, elevation, geology, plant types) on drought sensitivity. Our domain (15 15 km) includes four drainages within the East Water watershed near Gothic, Colorado, USA. We define foresummer drought sensitivity based on the regression slopes of the annual peak NDVI against the June Palmer Drought Severity Index between 1992 and 2010. Results show that foresummer drought sensitivity is spatially heterogeneous, and primarily dependent on the plant type and elevation. In support of the plot-based studies, we find that years with earlier snowmelt and drier foresummer conditions lead to lower peak NDVI; particularly in the low-elevation regions. Using random forest analysis, we identify additional key controls related to surface energy exchanges (i.e. potential net radiation), hydrological processes (i.e. microtopography and slope), and underlying geology. This remote-sensing-based approach for quantifying foresummer drought sensitivity can be used to identify the regions that are vulnerable or resilient to climate perturbations, as well as to inform future sampling, characterization, and modeling studies.
23 citations
TL;DR: It is shown that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and a causal transcript at an insulin-resistant T2D risk locus.
Abstract: Author(s): Manning, Alisa K; Goustin, Anton Scott; Kleinbrink, Erica L; Thepsuwan, Pattaraporn; Cai, Juan; Ju, Donghong; Leong, Aaron; Udler, Miriam S; Brown, James Bentley; Goodarzi, Mark O; Rotter, Jerome I; Sladek, Robert; Meigs, James B; Lipovich, Leonard | Abstract: AimsCausal transcripts at genomic loci associated with type 2 diabetes (T2D) are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin-resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, LOC157273, located 175 kilobases from PPP1R3B, which encodes a key protein regulating insulin-mediated hepatic glycogen storage in humans. We hypothesized that LOC157273 regulates expression of PPP1R3B in human hepatocytes.MethodsWe tested our hypothesis using Stellaris fluorescent in situ hybridization to assess subcellular localization of LOC157273; small interfering RNA (siRNA) knockdown of LOC157273, followed by RT-PCR to quantify LOC157273 and PPP1R3B expression; RNA-seq to quantify the whole-transcriptome gene expression response to LOC157273 knockdown; and an insulin-stimulated assay to measure hepatocyte glycogen deposition before and after knockdown.ResultsWe found that siRNA knockdown decreased LOC157273 transcript levels by approximately 80%, increased PPP1R3B mRNA levels by 1.7-fold, and increased glycogen deposition by g50% in primary human hepatocytes. An A/G heterozygous carrier (vs. three G/G carriers) had reduced LOC157273 abundance due to reduced transcription of the A allele and increased PPP1R3B expression and glycogen deposition.ConclusionWe show that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and a causal transcript at an insulin-resistant T2D risk locus.
20 citations
07 Aug 2020
TL;DR: A new sequential imputation algorithm for imputing missing values in spatio-temporal daily precipitation records is developed and shown that for reliable imputation, having a few strongly correlated references is more effective than having a larger number of weakly correlated references.
Abstract: Meteorological records, including precipitation, commonly have missing values. Accurate imputation of missing precipitation values is challenging, however, because precipitation exhibits a high degree of spatial and temporal variability. Data-driven spatial interpolation of meteorological records is an increasingly popular approach in which missing values at a target station are imputed using synchronous data from reference stations. The success of spatial interpolation depends on whether precipitation records at the target station are strongly correlated with precipitation records at reference stations. However, the need for reference stations to have complete datasets implies that stations with incomplete records, even though strongly correlated with the target station, are excluded. To address this limitation, we develop a new sequential imputation algorithm for imputing missing values in spatio-temporal daily precipitation records. We demonstrate the benefits of sequential imputation by incorporating it within a spatial interpolation based on a Random Forest technique. Results show that for reliable imputation, having a few strongly correlated references is more effective than having a larger number of weakly correlated references. Further, we observe that as the proportion of stations with incomplete records increases, there is a higher percentage of stations that benefit from sequential imputation. Overall, we present a new approach for imputing missing precipitation data which may also apply to other meteorological variables.
19 citations
TL;DR: The experimental evaluation shows that the proposed TRNG enables the generation of high-quality random bits that passed 12 tests in the National Institute of Standards and Technology statistical test suite without complex external circuits for post-processing.
Abstract: In this paper, we propose and demonstrate a novel technique for true random number generator (TRNG) application using GeSe-based Ovonic threshold switching (OTS) selector devices. The inherent variability in OTS threshold voltage results in a bimodal distribution of on/off states which can be easily converted into digital bits. The experimental evaluation shows that the proposed TRNG enables the generation of high-quality random bits that passed 12 tests in the National Institute of Standards and Technology statistical test suite without complex external circuits for post-processing. The randomness is further evidenced by the prediction rate of ~ 50% using machine learning algorithm. Compared with the TRNGs based on non-volatile memories, the volatile nature of OTS avoids the reset operation, thus further simplifying the operation and improving the generation frequency.
19 citations
TL;DR: It is discovered that interactions between neurotransmitters in mouse prefrontal cortex were altered during isoflurane anesthesia relative to wakefulness, extending to the neurochemical domain the concept that anesthetic-induced loss of wakefulness results from a disruption of neural network connectivity.
Abstract: This study discovered that interactions between neurotransmitters in mouse prefrontal cortex were altered during isoflurane anesthesia relative to wakefulness. Machine learning further demonstrated...
TL;DR: This work presents a novel and experimentally verified “True Random Number Generator” that uses exclusively conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bitrate, and power consumption.
Abstract: The future security of Internet of Things is a key concern in the cyber-security field. One of the key issues is the ability to generate random numbers with strict power and area constrains. "True Random Number Generators" have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified "True Random Number Generator" that uses exclusively conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bitrate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time multi-level and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bitrates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by the LSTM neural network.
TL;DR: An annotation structure that captures the overall experimental design as well as the relevant details of the steps from the biological sample to the library preparation, the sequencing procedure, and the sequencing and processed files is developed and implemented in a user-hosted web platform.
Abstract: Author(s): Hortenhuber, Matthias; Mukarram, Abdul K; Stoiber, Marcus H; Brown, James B; Daub, Carsten O | Abstract: BackgroundOver the past few years the variety of experimental designs and protocols for sequencing experiments increased greatly. To ensure the wide usability of the produced data beyond an individual project, rich and systematic annotation of the underlying experiments is crucial.FindingsWe first developed an annotation structure that captures the overall experimental design as well as the relevant details of the steps from the biological sample to the library preparation, the sequencing procedure, and the sequencing and processed files. Through various design features, such as controlled vocabularies and different field requirements, we ensured a high annotation quality, comparability, and ease of annotation. The structure can be easily adapted to a large variety of species. We then implemented the annotation strategy in a user-hosted web platform with data import, query, and export functionality.ConclusionsWe present here an annotation structure and user-hosted platform for sequencing experiment data, suitable for lab-internal documentation, collaborations, and large-scale annotation efforts.
TL;DR: It is concluded that rhizobiome community composition is influenced by competition for limiting nutrients, with implications for growth and development of the plant.
Abstract: The rhizosphere microbiome (rhizobiome) plays a critical role in plant health and development. However, the processes by which the constituent microbes interact to form and maintain a community are not well understood. To investigate these molecular processes, we examined pairwise interactions between 11 different microbial isolates under select nutrient-rich and nutrient-limited conditions. We observed that when grown with media supplemented with 56 mM glucose, two microbial isolates were able to inhibit the growth of six other microbes. The interaction between microbes persisted even after the antagonistic microbe was removed, upon exposure to spent media. To probe the genetic basis for these antagonistic interactions, we used a barcoded transposon library in a proxy bacterium, Pseudomonas putida, to identify genes which showed enhanced sensitivity to the antagonistic factor(s) secreted by Acinetobacter sp. 02. Iron metabolism-related gene clusters in P. putida were implicated by this systems-level analysis. The supplementation of iron prevented the antagonistic interaction in the original microbial pair, supporting the hypothesis that iron limitation drives antagonistic microbial interactions between rhizobionts. We conclude that rhizobiome community composition is influenced by competition for limiting nutrients, with implications for growth and development of the plant.
TL;DR: It is shown that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and the causal transcript at an insulin resistant type 2 diabetes risk locus.
Abstract: Aims: Causal transcripts at genomic loci associated with type 2 diabetes are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, LOC157273, located 175 kilobases from PPP1R3B, which encodes a key protein regulating insulin-mediated hepatic glycogen storage in humans. We hypothesized that LOC157273 regulates expression of PPP1R3B in human hepatocytes.
Methods: We tested our hypothesis using Stellaris fluorescent in-situ hybridization to assess subcellular localization of LOC157273; siRNA knockdown of LOC157273, followed by RT-PCR to quantify LOC157273 and PPP1R3B expression; RNA-seq to quantify the whole-transcriptome gene expression response to LOC157273 knockdown and an insulin-stimulated assay to measure hepatocyte glycogen deposition before and after knockdown.
Results: We found that siRNA knockdown decreased LOC157273 transcript levels by approximately 80%, increased PPP1R3B mRNA levels by 1.7-fold and increased glycogen deposition by >50% in primary human hepatocytes. An A/G heterozygous carrier (vs. three G/G carriers) had reduced LOC157273 abundance due to reduced transcription of the A allele and increased PPP1R3B expression and glycogen deposition.
Conclusion: We show that the lncRNA LOC157273 is a negative regulator of PPP1R3B expression and glycogen deposition in human hepatocytes and the causal transcript at an insulin resistant type 2 diabetes risk locus.
TL;DR: It is concluded that rhizobiome community composition is influenced by competition for limiting nutrients with implications for growth and development of the plant.
Abstract: The rhizosphere microbiome (rhizobiome) plays a critical role in plant health and development. However the processes by which the constituent microbes interact to form and maintain a community are not well understood. To investigate these molecular processes, we examined pairwise interactions between 11 different microbial isolates under selected nutrient-rich and nutrient-limited conditions. We observed that when grown with media supplemented with 56 mM glucose, 2 microbial isolates were able to inhibit the growth of 6 out of 11 other microbes tested. The interaction between microbes persisted even after the antagonistic microbe was removed, upon exposure to spent media. To probe the genetic basis for these antagonistic interactions, we used a barcoded transposon library in a proxy bacterium, Pseudomonas putida, to identify genes which showed enhanced sensitivity to the antagonistic factor(s) secreted by Acinetobacter sp. 02. Iron metabolism-related gene clusters in P. putida were implicated by this systems-level analysis. The supplementation of iron prevented the antagonistic interaction in the original microbial pair supporting the hypothesis that iron limitation drives antagonistic microbial interactions between rhizobionts. We conclude that rhizobiome community composition is influenced by competition for limiting nutrients with implications for growth and development of the plant.
26 Jun 2020
TL;DR: In this article, the authors proposed a new solution on TRNG using random telegraph noise (RTN) including the benefits and the disadvantages, and performed security check using the NIST randomness tests for both the RTN-based TRNG and various conventional pseudo random umber generator.
Abstract: True Random number Generator (TRNG) is critical for secure communications. In this work, we explain in details regarding our recent solution on TRNG using random telegraph noise (RTN) including the benefits and the disadvantages. Security check is performed using the NIST randomness tests for both the RTN-based TRNG and various conventional pseudo random umber generator. The newly-proposed design shows excellent randomness, power consumption, low design complexity, small area and high speed, making it a suitable candidate for future cryptographically secured applications within the internet of things.
TL;DR: The overexpression of hypoxia induced factor 1a/2a in ccRCC leads to up-regulation of vascular endothelial growth factor (VEGF) that results in increased angiogenesis.
TL;DR: Proactive identification of potential challenges at the design and planning stages of test evaluation trials will enable strategies to improve trial design and management that may be different from standard strategies used for intervention trials.
Abstract: Test evaluation trials present different challenges for trial managers compared to intervention trials. There has been very little research on the management of test evaluation trials and how this impacts on trial success, in comparison with intervention trials. Evaluations of medical tests present specific challenges, because they are a pivot point bridging the complexities of pathways prompting testing with treatment decision-making. We systematically explored key differences in the trial design and management of test evaluation trials compared to intervention trials at the different stages of study design and delivery. We identified challenges in test evaluation trials that were more pronounced than in intervention trials, based on experience from 10 test evaluation trials. We formed a focus group of 7 trial managers and a statistician who had been involved in the day-to-day management of both test evaluation trials and intervention trials. We used discussion and content analysis to group challenges from 10 trials into a structured thematic format. The trials covered a range of medical conditions, diagnostic tests, clinical pathways and conditions including chronic kidney disease, chronic pelvic pain, colitis, detrusor over-activity, group B streptococcal colonisation, tuberculosis and colorectal, lung, ovarian and thyroid cancers. We identified 10 common themes underlying challenges that are more pronounced in test evaluation compared to intervention trials. We illustrate these themes with examples from 10 trials, including with 31 specific challenges we experienced. The themes were ethics/governance; accessing patient populations; recruitment; patient preference; test processes, clinical pathways and samples storage; uncertainty of diagnostic results; verifying diagnosis (reference standard); follow-up; adverse effects; and diagnostic impact. We present 10 common themes, including 31 challenges, in test evaluation trials that will be helpful to others designing and managing future test evaluation trials. Proactive identification of potential challenges at the design and planning stages of test evaluation trials will enable strategies to improve trial design and management that may be different from standard strategies used for intervention trials. Future work could extend this topic to include challenges for other trial stakeholders including participants, clinicians, statisticians and funders. All trials reviewed in this project were registered and are provided in Table 1.