Biology subjects

Tripathi, A.

Publications and source records attributed to Tripathi, A..

65 records · Page 4Linked to original sources

bioRxiv2020

Overcoming the inhibitory microenvironment surrounding oligodendrocyte progenitor cells following demyelination

Chronic demyelination in the human CNS is characterized by an inhibitory microenvironment that impairs recruitment and differentiation of oligodendrocyte progenitor cells (OPCs) leading to failed remyelination and axonal atrophy. By network-based transcriptomics, we identified sulfatase 2 (Sulf2) mRNA in activated human primary OPCs. Sulf2, an extracellular endosulfatase, modulates the signaling microenvironment by editing the pattern of sulfation on heparan sulfate proteoglycans. We found that Sulf2 was increased in demyelinating lesions in multiple sclerosis and was actively secreted by human OPCs. In experimental demyelination, elevated OPC Sulf1/2 expression directly impaired progenitor recruitment and subsequent generation of oligodendrocytes thereby limiting remyelination. Sulf1/2 potentiates the inhibitory microenvironment by promoting BMP and WNT signaling in OPCs. Importantly, pharmacological sulfatase inhibition using PI-88 accelerated oligodendrocyte recruitment and remyelination by blocking OPC-expressed sulfatases. Our findings define an important inhibitory role of Sulf1/2 and highlight the potential for modulation of the heparanome in the treatment of chronic demyelinating disease.

neuroscience↗

bioRxiv2019

Metabolome-informed microbiome analysis refines metadata classifications and reveals unexpected medication transfer in captive cheetahs

Structured AbstractEven high-quality collection and reporting of study metadata in microbiome studies can lead to various forms of inadvertently missing or mischaracterized information that can alter the interpretation or outcome of the studies, especially with non-model organisms. Metabolomic profiling of fecal microbiome samples can provide empirical insight into unanticipated confounding factors that are not possible to obtain even from detailed care records. We illustrate this point using data from cheetahs from the San Diego Zoo Safari Park. The metabolomic characterization indicated that one cheetah had to be moved from the non-antibiotic-exposed to the antibiotic-exposed group. The detection of the antibiotic in this second cheetah was likely due to grooming interactions with the cheetah that was administered antibiotics. Similarly, because transit time for stool is variable, early fecal samples within the first few days of antibiotic prescription do not all contain detectable antibiotics. Therefore, the microbiome is not affected by the antibiotics at those time points. These insights significantly altered the way the samples were grouped for analysis (antibiotic vs no antibiotic), and the subsequent understanding of the effect of the antibiotics on the cheetah microbiome. Metabolomics also revealed information about numerous other medications, and provided unexpected dietary insights that in turn improved our understanding of the molecular patterns on the impact on the community microbial structure. These results suggest that untargeted metabolomics data provide empirical evidence to correct records of non-model organisms in captivity, although we also expect these methods will be appropriate for experimental conditions typical in human studies.\n\nImportanceMetabolome-informed analyses can enhance omics studies by enabling the correct partitioning of samples by identifying hidden confounders inadvertently misrepresented or omitted from carefully curated metadata. We demonstrate the utility of metabolomics in a study characterizing the microbiome associated with liver disease in cheetahs. Metabolome-informed reinterpretation of metagenome and metabolome profiles factored in an unexpected transfer of antibiotics preventing misinterpretation of the data. Our work suggests that untargeted metabolomics can be used to verify, augment, and correct sample metadata to support improved grouping of sample data for microbiome analyses, here for non-model organisms in captivity. However, the techniques also suggest a path forward for correcting clinical information in human studies to enable higher-precision analyses.

systems biology↗

bioRxiv2019

Non-Canonical Regulation of Phosphatidylserine Metabolism by a Phosphatidylinositol Transfer Protein and a Phosphatidylinositol 4-OH Kinase

The phosphatidylserine (PtdSer) decarboxylase Psd2 is proposed to engage in an endoplasmic reticulum (ER)-Golgi/endosome membrane contact site (MCS) that facilitates phosphatidylserine decarboxylation to phosphatidylethanomaine (PtdEtn) in Saccharomyces cerevisiae. While this MCS is envisioned to consist of Psd2, the Sec14-like phosphatidylinositol transfer protein (PITP) Sfh4, the Stt4 phosphatidylinositol (PtdIns) 4-OH kinase, the Scs2 tether, and at least one other uncharacterized protein, functional data that address key foundations of this model are sparse. We now report that Psd2, Sfh4 and Stt4 are the only components individually required for biologically sufficient Psd2-dependent PtdEtn production. Surprisingly, neither the PtdIns-transfer activity of Sfh4 nor its capacity to activate Stt4 is required to stimulate the Psd2 pathway. Instead, Sfh4 activates the Psd2 pathway via a specific Sfh4-Psd2 physical interaction. Whereas the data indicate an Sfh4-independent association of Stt4 with Psd2 as well, we find Stt4 also regulates Psd2 activity indirectly by influencing the PtdSer pool accessible to Psd2 for decarboxylation. These collective results demonstrate that the proposed ER-Golgi/endosomal MCS model fails to provide an accurate description of the Psd2 system in yeast, and provide an example where the biological function of a Sec14-like PITP is uncoupled from its canonical activity as a PtdIns transfer protein.

cell biology↗

bioRxiv2019

Chemical Impacts of the Microbiome Across Scales Reveal Novel Conjugated Bile Acids

A mosaic of cross-phyla chemical interactions occurs between all metazoans and their microbiomes. In humans, the gut harbors the heaviest microbial load, but many organs, particularly those with a mucosal surface, associate with highly adapted and evolved microbial consortia1. The microbial residents within these organ systems are increasingly well characterized, yielding a good understanding of human microbiome composition, but we have yet to elucidate the full chemical impact the microbiome exerts on an animal and the breadth of the chemical diversity it contributes2. A number of molecular families are known to be shaped by the microbiome including short-chain fatty acids, indoles, aromatic amino acid metabolites, complex polysaccharides, and host lipids; such as sphingolipids and bile acids3-11. These metabolites profoundly affect host physiology and are being explored for their roles in both health and disease. Considering the diversity of the human microbiome, numbering over 40,000 operational taxonomic units12, a plethora of molecular diversity remains to be discovered. Here, we use unique mass spectrometry informatics approaches and data mapping onto a murine 3D-model13-15 to provide an untargeted assessment of the chemical diversity between germ-free (GF) and colonized mice (specific-pathogen free, SPF), and report the finding of novel bile acids produced by the microbiome in both mice and humans that have evaded characterization despite 170 years of research on bile acid chemistry16.

microbiology↗

bioRxiv2019

DDAP: docking domain affinity and biosynthetic pathway prediction tool for type I polyketide synthases

SummaryDDAP is a tool for predicting the biosynthetic pathways of the products of type I modular polyketide synthase (PKS) with the focus on providing a more accurate prediction of the ordering of proteins and substrates in the pathway. In this study, the module docking domain (DD) affinity prediction performance on a hold-out testing data set reached AUC = 0.88; the MRR of pathway prediction reached 0.67. DDAP has advantages compared to previous informatics tools in several aspects: (i) it does not rely on large databases, making it a high efficiency tool, (ii) the predicted DD affinity is represented by a probability (0 to 1), which is more intuitive than raw scores, (iii) its performance is competitive compared to the current popular rule-based algorithm. To the best of our knowledge, DDAP is so far the first machine learning based algorithm for type I PKS pathway prediction. We also established the first database of type I modular PKSs, featuring a comprehensive annotation of available docking domains information in bacterial biosynthetic pathways.\n\nAvailability and implementationThe DDAP database is available at https://tylii.github.io/ddap. The prediction algorithm DDAP is freely available on GitHub (https://github.com/tylii/ddap) and released under the MIT license.\n\nContactukarvind@umich.edu

bioinformatics↗

bioRxiv2018

Generation of Transgenic Human Malaria Parasites With Strong Fluorescence in the Transmission Stages

Malaria parasites have a complex life cycle that includes specialized stages for transmission between their mosquito and human hosts. These stages are an understudied part of the lifecycle yet targeting them is an essential component of the effort to shrink the malaria map. The human parasite Plasmodium falciparum is responsible for the majority of deaths due to malaria. Our goal was to generate transgenic P. falciparum lines that could complete the lifecycle and produce fluorescent transmission stages for more in-depth and high-throughput studies. Using zinc-finger nuclease technology to engineer a marker-free integration site, we generated three transgenic P. falciparum lines in which tdtomato or gfp were stably integrated into the genome. Expression was driven by either stage-specific peg4 and csp promoters or the constitutive ef1a promoter. Phenotypic characterization of these lines demonstrates that they complete the life cycle with high infection rates and give rise to fluorescent mosquito stages. The transmission stages are sufficiently bright for intra-vital imaging, flow cytometry and scalable screening of chemical inhibitors and potentially inhibitory antibodies.

microbiology↗

bioRxiv2018

The Cuon Enigma: Genome survey and comparative genomics of the endangered Dhole (Cuon alpinus)

The Asiatic wild dog is an endangered monophyletic canid restricted to Asia; facing threats from habitat fragmentation and other anthropogenic factors. Dholes have unique adaptations as compared to other wolf-like canids for large litter size (larger number of mammae) and hypercarnivory making it evolutionarily notable. Over evolutionary time, dhole and the subsequent divergent wild canids have lost coat patterns found in African wild dog. Here we report the first high coverage genome survey of Asiatic wild dog and mapped it with African wild dog, dingo and domestic dog to assess the structural variants. We generated a total of 124.8 Gb data from 416140921 raw read pairs and retained 398659457 reads with 52X coverage and mapped 99.16% of the clean reads to the three reference genomes. We identified ~13553269 SNVs, ~2858184 InDels, ~41000 SVs, ~1854109 SSRs and about 1000 CNVs. We compared the annotated genome of dingo and domestic dog with dhole genome sequence to understand the role of genes responsible in pelage pattern, dentition and mammary glands. Positively selected genes for these phenotypes were looked for SNP variants and top ranked genes for coat pattern, dentition and mammary glands were found to play a role in signalling and developmental pathways. Mitochondrial genome assembly predicted 35 genes, 11 CDS and 24 tRNA. This genome information will help in understanding the divergence of two monophlyletic canids, Cuon and Lycaon, and the evolutionary adaptations of dholes with respect to other canids.

genomics↗

bioRxiv2018

Petrobactin protects against oxidative stress and enhances sporulation efficiency in Bacillus anthracis Sterne

Bacillus anthracis is a gram-positive bacillus that under conditions of environmental stress, such as low nutrients, can convert from a vegetative bacillus to a highly durable spore that enables long-term survival. The sporulation process is regulated by a sequential cascade of dedicated transcription factors but requires key nutrients to complete, one of which is iron. Iron acquisition by the iron-scavenging siderophore petrobactin is the only such system known to be required for vegetative growth of B. anthracis in iron-depleted conditions, e.g., in the host. However, the extent to which petrobactin is involved in spore formation is unknown. This work shows that efficient in vitro sporulation of B. anthracis requires petrobactin, that the petrobactin biosynthesis operon (asbA-F) is induced prior to sporulation, and that petrobactin itself is associated with spores. Petrobactin is also required for both oxidative stress protection during late stage growth and wild-type levels of sporulation in sporulation medium. When considered with the petrobactin-dependent sporulation in bovine blood also described in this work, these effects on in vitro growth and sporulation suggest that petrobactin is required for B. anthracis transmission via the spore during natural infections in addition to its key functions during active anthrax infections.\n\nImportanceBacillus anthracis causes the disease anthrax, which is transmitted via its dormant, spore phase. However, converting from bacilli to spore is a complex, energetically costly process that requires many nutrients including iron. B. anthracis requires the siderophore petrobactin to scavenge iron from host environments. We show that in the Sterne strain, petrobactin is required also for efficient sporulation, even when ample iron is available. The petrobactin biosynthesis operon is expressed during sporulation, and petrobactin is biosynthesized during growth in high iron sporulation medium but instead of being exported, the petrobactin remains intracellular to protect against oxidative stress and improve sporulation. It is also required for full growth and sporulation in blood (bovine), an essential step for anthrax transmission between mammalian hosts.

microbiology↗

bioRxiv2018

Untargeted Mass Spectrometry-Based Metabolomics Tracks Molecular Changes in Raw and Processed Foods and Beverages

A major aspect of our daily lives is the need to acquire, store and prepare our food. Storage and preparation can have drastic effects on the compositional chemistry of our foods, but we have a limited understanding of the temporal nature of processes such as storage, spoilage, fermentation and brewing on the chemistry of the foods we eat. Here, we performed a temporal analysis of the chemical changes in foods during common household preparations using untargeted mass spectrometry and novel data analysis approaches. Common treatments of foods such as home fermentation of yogurt, brewing of tea, spoilage of meats and ripening of tomatoes altered the chemical makeup through time, through both chemical and biological processes. For example, brewing tea altered its composition by increasing the diversity of molecules, but this change was halted after 4 min of brewing. The results indicate that this is largely due to differential extraction of the material from the tea and not modification of the molecules during the brewing process. This is in contrast to the preparation of yogurt from milk, spoilage of meat and the ripening of tomatoes where biological transformations directly altered the foods molecular composition. Comprehensive assessment of chemical changes using multivariate statistics showed the varied impacts of the different food treatments, while analysis of individual chemical changes show specific alterations of chemical families in the different food types. The methods developed here represent novel approaches to studying the changes in food chemistry that can reveal global alterations in chemical profiles and specific transformations at the chemical level.\n\nO_LSTHighlightsC_LSTO_LIWe created a reference data set for tomato, milk to yogurt, tea, coffee, turkey and beef.\nC_LIO_LIWe show that normal preparation and handling affects the molecular make-up.\nC_LIO_LITea preparation is largely driven by differential extraction.\nC_LIO_LIFormation of yogurt involves chemical transformations.\nC_LIO_LIThe majority of meat molecules are not altered in 5 days at room temperature.\nC_LI

biochemistry↗

bioRxiv2016

A Pilot Study: Development of a Reference Spatiotemporal Gait Data Set for Indian Subjects.

1.Interpretation of pathological gait has, for decades, offered insight into amputee anomalies and diseases such as cerebral palsy. Gait analysis has been actively used at the Bhagwan Mahaveer Viklang Sahatya Samiti for such purposes. The normative gait data used to compare data obtained from amputees, however, has been collected from laboratories under dissimilar conditions, skewing interpretation. Spatiotemporal gait parameters were extractedfrom 43 male Indian subjects using a 7.5m walkway and the BTS Bioengineering GAITLAB setup. Working under the hypothesis that a lack of cross-cultural validity was somewhat responsible for variations in normative gait, we attempted to develop a region-specific data set for use at the headquarters of the Jaipur Foot Organization Bhagwan Mahaveer Viklang Sahatya Samiti (BMVSS). Stratified random sampling was used to recruit subjects and measures were taken to ensure minimal effects of extraneous variables. Statistical analysis was performed on obtained data using one-way analysis of variance (ANOVA) to gauge the effect age and ethnicity had on normative values of the parameters investigated. We found statistically significant p-values for a few spatiotemporal parameters in the analysis of variance for both age and ethnicity. While the results were much less significant than initially hypothesized, the study proved an efficient way to create a normative gait data set exclusively for use at the gait laboratory of the Jaipur Foot Organization, thereby eliminating potential erroneous interpretation of pathological gait when comparing said gait to normative gait data obtained in laboratories under dissimilar conditions.

bioengineering↗

bioRxiv2016

A Probabilistic Approach to the Detection and Diagnosis of Obstructive Sleep Apnea and Its Environmental Factors Using Chest Movement Analysis, Recursive Noise Reduction and Machine Learning Algorithms.

1In a novel approach to diagnose Obstructive Sleep Apnea, electronic components, such as an Arduino Mega, a Bluetooth Transceiver, an accelerometer, and a air-quality sensor, were put together to create a wearable that would detect the frequency of apnea events, detect and diagnose the disorder, and sound an alarm when necessary. A primary consideration was to make the mechanism accessible and affordable, and in doing so, lower the cases of Obstructive Sleep Apnea that go undiagnosed due to the cost and inconvenience associated with the traditional diagnosis method--a Polysomnogram. Bluetooth capability was an additional consideration so that the device would transmit data directly to an android smartphone, eliminating the need for an additional output mechanism. The total cost of the device, quite surprisingly, did not exceed $30, and therein rendered the device an accessible, affordable mechanism for diagnosis. Tests of the device on diagnosed patients yielded data consistent with the diagnosis, with a few false positives as a result of the excessive sensitivity of the sensors.

biophysics↗