Biology subjects

Jordan, B.

Publications and source records attributed to Jordan, B..

8 recordsLinked to original sources

bioRxiv2025

Transcription profiling and functional analysis of spRNAs and their corresponding asRNAs in Methanosarcina mazei

Small proteins (sPs) encoded by small RNAs (sRNAs), the so-called small protein RNAs (spRNAs), and their corresponding antisense RNAs (asRNAs) have emerged as important regulatory elements in microbial stress adaptation, yet remain poorly characterized in archaea. In this study, we identified and characterized five sRNA/asRNA pairs in the methanoarchaeon Methanosarcina mazei. Expression analysis revealed condition-specific regulation of two of those pairs, spRNA23/asRNA93 and spRNA24/asRNA94, under oxidative, temperature, and osmotic stress. Overexpression of the corresponding small proteins, sP23 and sP24, revealed distinct physiological effects: both enhanced growth under high-salt conditions, while sP24 in addition supported cell size maintenance during osmotic stress, as confirmed by transmission electron microscopy. Consistently, overexpression of asRNA94 let to impaired growth under salt stress, suggesting its negative regulatory role towards sP24. The results also imply that the antisense RNA might be crucial for controlling sP24 expression under non-stress conditions. Bioinformatic analysis predicted one transmembrane domain in sP24. Membrane-association of sP24 was experimentally validated in vitro using a cell-free expression system, demonstrating sP24s integration into lipid bilayers. Conservation analysis showed that spRNA24 appears specific for M. mazei strains potentially reflecting niche adaptation, while spRNA23 is widespread within Methanosarcina. These findings demonstrate that archaeal sRNAs can encode functional small proteins, often encoded together with their respective regulatory asRNA, that contribute to environmental stress responses, overall offering new insights into the role of sRNA-derived small proteins in archaea.

microbiology↗

bioRxiv2024

Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity

Long-read RNA sequencing has shed light on transcriptomic complexity, but questions remain about the functionality of downstream protein products. We introduce Biosurfer, a computational approach for comparing protein isoforms, while systematically tracking the transcriptional, splicing, and translational variations that underlie differences in the sequences of the protein products. Using Biosurfer, we analyzed the differences in 32,799 pairs of GENCODE annotated protein isoforms, finding a majority (70%) of variable N-termini are due to the alternative transcription start sites, while only 9% arise from 5 UTR alternative splicing. Biosurfers detailed tracking of nucleotide-to-residue relationships helped reveal an uncommonly tracked source of single amino acid residue changes arising from the codon splits at junctions. For 17% of internal sequence changes, such split codon patterns lead to single residue differences, termed "ragged codons". Of variable C-termini, 72% involve splice- or intron retention-induced reading frameshifts. We found an unusual pattern of reading frame changes, in which the first frameshift is closely followed by a distinct second frameshift that restores the original frame, which we term a "snapback" frameshift. We analyzed long read RNA-seq-predicted proteome of a human cell line and found similar trends as compared to our GENCODE analysis, with the exception of a higher proportion of isoforms predicted to undergo nonsense-mediated decay. Biosurfers comprehensive characterization of long-read RNA-seq datasets should accelerate insights of the functional role of protein isoforms, providing mechanistic explanation of the origins of the proteomic diversity driven by the alternative splicing. Biosurfer is available as a Python package at https://github.com/sheynkman-lab/biosurfer.

genomics↗

bioRxiv2022

Using Watershed Characteristics for Improving Fecal Source Identification

Fecal pollution is one of the most prevalent forms of pollution affecting waterbodies worldwide, threatening public health, and negatively impacting aquatic environments. Microbial source tracking (MST) applies polymerase chain reaction (PCR) technology to help identify the source of fecal pollution. In this study, we combine spatial data for two watersheds with general and host-specific MST markers to target human, bovine, and general ruminant sources. Two different PCR technologies were applied for quantifying the targets: quantitative PCR (qPCR) and droplet digital PCR (ddPCR). We found that ddPCR had a higher detection rate (75%) of quantifiable samples compared to qPCR (27%), indicating that ddPCR is more sensitive than qPCR. The three host-specific markers were detected at all sites (n=25), suggesting that humans, cows, and ruminants are contributing to fecal contamination in these watersheds. MST results, combined with watershed characteristics, suggest that streams draining areas with low-infiltration soil groups, high septic system prevalence, and high agricultural land use are at an increased risk for fecal contamination. Microbial source tracking has been applied in numerous studies to aid in identifying the sources of fecal contamination, however these studies usually lack information on the involvement of watershed characteristics. Our study combined watershed characteristics with MST results, applying more sensitive PCR techniques, in addition to watershed characteristics to provide more comprehensive insight into the factors that influence fecal contamination in order to implement the most effective best management practices. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/496426v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@13ca50forg.highwire.dtl.DTLVardef@78a781org.highwire.dtl.DTLVardef@13d0664org.highwire.dtl.DTLVardef@16ec950_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIddPCR provided higher sensitivity over qPCR when analyzing environmental samples C_LIO_LIHuman markers had an association with the number of septic systems in a watershed C_LIO_LIEvery site had positive detections for all FIB markers C_LIO_LIBoth ruminant markers were associated with low infiltration hydrologic soil groups C_LIO_LICombining watershed characteristics with MST testing improved source identification C_LI

microbiology↗

bioRxiv2021

KSTAR: An algorithm to predict patient-specific kinase activities from phosphoproteomic data

Kinase inhibitors are one of the largest classes of FDA-approved drugs and are major targets in oncology. Although kinase inhibitors have played an important role in improving cancer outcomes, major challenges still exist, including the development of resistance and failure to respond to treatments. Improvements for tumor profiling of kinase activity would be an important step in improving treatment outcomes and identifying effective kinase targets. Here, we present a graph- and statistics-based algorithm, called KSTAR, which harnesses the phosphoproteomic profiling of human cells and tissues by predicting kinase activity profiles from the observed phosphorylation of kinase substrates. The algorithm is based on the hypothesis that the more active a kinase is, the more of its substrates will be observed in a phosphoproteomic experiment. This method is error- and bias-aware in its approach, overcoming challenges presented by the variability of phosphoproteomic pipelines, limited information about kinase-substrate relationships, and limitations of global kinase-substrate predictions, such as training set bias and high overlap between predicted kinase networks. We demonstrate that the predicted kinase activities: 1) reproduce physiologically-relevant expectations and generates novel hypotheses within cell-specific experiments, 2) improve the ability to compare phosphoproteomic samples on the same tissues from different labs, and 3) identify tissue-specific kinase profiles. Global benchmarking and comparison to other algorithms demonstrates that KSTAR is particularly superior for predicting tyrosine kinase activities and, given its focus on utilizing more of the available phosphoproteomic data, significantly less sensitive to study bias. Finally, we apply the approach to complex human tissue biopsies in breast cancer, where we find that KSTAR activity predictions complement current clinical standards for identifying HER2-status - KSTAR can identify clinical false positives, patients who will fail to respond to inhibitor therapy, and clinically defined HER2-negative patients that might benefit from HER2-targeted therapy. KSTAR will be useful for both basic biological understanding of signaling networks and for improving clinical outcomes through improved clinical trial design, identification of new and/or combination therapies, and for identifying the failure to respond to targeted kinase therapies.

systems biology↗

bioRxiv2021

Fenbendazole resistance in Heterakis gallinarum, the vector of Histomonas meleagridis, the causative agent of Blackhead Disease in poultry.

Due to their ubiquity, management of parasites is a common and important factor for profitable production of poultry. Heterakis gallinarum, the cecal nematode, is the most common nematode parasite of poultry. While typically causing no pathology on its own, H. gallinarum is the vector of Histomonas meleagridis, a protozoan parasite that causes blackhead disease. Histomonas meleagridis is highly pathogenic in turkeys, potentially causing high mortality. In contrast, disease caused by H. meleagridis is much less severe in chickens, where it primarily reduces productivity without manifestations of clinical disease. There are no approved treatments for H. meleagridis, making control reliant on control of the helminth vector through the use of fenbendazole (FBZ) the only drug labeled for treatment of H. gallinarum in the United States We were contacted by an industry veterinarian regarding health-related concerns in a broiler-breeder house due to histomoniasis, despite frequent anthelmintic treatments. Since we had recently diagnosed resistance to FBZ in Ascaridia dissimilis, a closely related nematode of turkeys, we were interested to determine if H. gallinarum had also evolved resistance to FBZ. Heterakis gallinarum eggs were isolated from litter collected from the house and used to infect 108 chickens. Treatment groups included a non-treated control, a label-dose and a 2X-label dose of FBZ, with 36 birds per group divided into two replicate pens of 18 birds each. Birds were placed at 1-day post hatch, and at 3 weeks of age were infected with 150 embryonated eggs via oral gavage. Two weeks post infection, treated birds were administered a minimum of either a label- or 2X label-dose of FBZ in water for 5 days (SafeGuard(R) Aquasol, 1mg/kg BW). To ensure that all birds consumed the full intended dose at a minimum, the dosage was calculated using 1.25 times the average body weight. One-week post treatment, birds were euthanized, ceca removed, and parasites enumerated. Efficacy was calculated by comparing the total numbers of worms recovered from each treatment group to the numbers recovered in the non-treated control group. There were no significant differences in worm numbers recovered from any of the three groups (p-value=0.81). There also was no efficacy benefit to treatment with a 2X dose; H. gallinarum worm counts were reduced by 42.7% and 41.4%, for the label and 2X dosages, respectively. These data provide strong evidence that H. gallinarum has developed resistance to FBZ. Consequently, in houses infected with FBZ-resistant H. gallinarum, H. meleagridis will be able to cycle through the birds in an unrestricted manner. Further investigation is needed to determine the prevalence of resistance in H. gallinarum on chicken farms, but it is clear this has the potential to have a large-scale economic impact on the poultry industry. These data when viewed together with our recent findings of FBZ resistance in A. dissimilis, suggest that drug resistance in ascarid nematodes may be an important emerging problem on poultry operations.

zoology↗

bioRxiv2021

Impact of fenbendazole resistance in Ascaridia dissimilis on the economics of production in turkeys

Feed conversion efficiency is among the most important factors affecting profitable production of poultry. Infections with parasitic nematodes can decrease efficiency of production, making parasite control through the use of anthelmintics an important component of health management. In ruminants and horses, anthelmintic resistance is highly prevalent in many of the most important nematode species, which greatly impacts their control. Recently, we identified resistance to fenbendazole in an isolate of Ascaridia dissimilis, the most common intestinal helminth of turkeys. Using this drug-resistant isolate, we investigated the impact that failure to control infections has on weight gain and feed conversion in growing turkeys. Birds were infected on Day 0 with either a fenbendazole-susceptible or -resistant isolate, and then half were treated with fenbendazole (SafeGuard(R) Aquasol) at 4- and 8-weeks post infection. Feed intake and bird weight were measured for each pen weekly throughout the study, and feed conversion rate was calculated. Necropsy was performed on birds from each treatment group to assess worm burdens at weeks 7 and 9 post infection. In the birds infected with the susceptible isolate, fenbendazole-treated groups had significantly better feed conversion as compared to untreated groups. In contrast, there were no significant differences in feed conversion between the fenbendazole-treated and untreated groups in the birds infected with the resistant isolate. At both weeks 7 and 9, worm burdens were significantly different between the treated and untreated birds infected with the drug-susceptible isolate, but not in the birds infected with the drug-resistant isolate. These significant effects on feed conversion were seen despite having a rather low worm establishment in the birds. Overall, these data indicate that A. dissimilis can produce significant reductions in feed conversion, and that failure of treatment due to the presence of fenbendazole-resistant worms can have a significant economic impact on turkey production. Furthermore, given the low worm burdens and an abbreviated grow out period of this study, the levels of production loss we measured may be an underestimate of the true impact that fenbendazole-resistant worms may have on a commercial operation.

zoology↗

bioRxiv2020

KinPred: A unified approach and resource for human kinase-substrate predictions

Tyrosine and serine/threonine kinases are essential regulators of cell processes and are important targets for human therapies. Unfortunately, very little is known about specific kinase-substrate relationships, making it difficult to infer meaning from dysregulated phosphoproteomic datasets or for researchers to identify possible kinases that regulate specific or novel phosphorylation sites. The last two decades have seen an explosion in algorithms to extrapolate from what little is known into the larger unknown - predicting kinase relationships with site-specific substrates using a variety of approaches that include the sequence-specificity of kinase catalytic domains and various other factors, such as evolutionary relationships, coexpression, and protein-protein interaction networks. Unfortunately, a number of limitations prevent researchers from easily harnessing these resources, such as loss of resource accessibility, limited information in publishing that results in a poor mapping to a human reference, and not being updated to match the growth of the human phosphoproteome. Here, we propose a methodological framework for publishing predictions in a unified way, which entails ensuring predictions have been run on a current reference proteome, mapping the same substrates and kinases across resources to a common reference, filtering for the human phosphoproteome, and providing methods for updating the resource easily in the future. We applied this framework on three currently available resources, published in the last decade, which provide kinase-specific predictions in the human proteome. Using the unified datasets, we then explore the role of study bias, the emergent network properties of these predictive algorithms, and comparisons within and between predictive algorithms. The combination of the code for unification and analysis, as well as the unified predictions are available under the resource we named KinPred. We believe this resource will be useful for a wide range of applications and establishes best practices for long-term usability and sustainability for new and existing predictive algorithms.

molecular biology↗

bioRxiv2020

Small protein 26 interacts and enhances glutamine synthetase activity in Methanosarcina mazei

Small ORFs (sORF) encoded small proteins have been overlooked for a long time due to challenges in prediction and distinguishing between coding and non-coding predicted sORFs and in their biochemical detection and characterization. We report on the first biochemical and functional characterization of a small protein (sP26) in the archaeal model organism Methanosarcina mazei, comprising 23 amino acids. The corresponding encoding leaderless mRNA (spRNA26) is highly conserved within numerous Methanosarcina strains on the amino acid as well as on nucleotide level strongly arguing for a cellular function of the small protein. spRNA26 is significantly enhanced under nitrogen limitation, but also under oxygen and salt stress conditions. His-tagged sP26 was heterologously expressed and purified by fractionated ammonium sulfate precipitation, affinity chromatography and size exclusion centrifugation. Using independent biochemical approaches (pull-down by affinity chromatography followed by MS analysis, revers pull-down, microscale thermophoresis and size exclusion chromatography) we observed that sP26 interacts and forms complexes with M. mazei glutamine synthetase (GlnA1) with high affinity (app. KD = 45 +/- 14 {micro}M). Upon interaction with sP26, GlnA1 activity was significantly stimulated independently and in addition to the known activation by the metabolite 2-oxoglutarate. Besides strong interaction of sP26 with the PII-like protein GlnK1 was demonstrated (KD= 1.4 {micro}M +/- 0.9 {micro}M). On the basis of these findings, we hypothesize that in addition to 2-oxoglutarate, sP26 activates GlnA1 activity under nitrogen limitation most likely by stabilizing the dodecameric structure of GlnA1.

biochemistry↗