Coxiella burnetii infection persistence in a goat herd during seven kidding seasons after an outbreak of abortions: the effect of vaccination.

Coxiella burnetii infection was monitored during seven kidding seasons (2017-2023) in a dairy goat herd that after an outbreak of Q fever abortions was vaccinated with an inactivated phase I vaccine. Due to the high infection rate just after the outbreak, only the replacement stock was vaccinated during the first three kidding seasons, and when the average herd immunity had decreased (fourth kidding season onwards), the whole herd was vaccinated. Vaginal swabs, feces, and milk were analyzed by PCR to monitor infection, and dust and aerosols were analyzed to measure C. burnetii environmental contamination. One year after the onset of the outbreak, a significant reduction in C. burnetii shedding loads was observed, but the percentage of shedding animals remained high until the third kidding season. By the seventh kidding season, no shedders were detected. The bacterial load excreted was significantly lower in vaccinated compared with unvaccinated animals, and in yearlings compared with multiparous. C. burnetii was detected by PCR in aerosols collected inside the animal premises throughout the study period except in the last season; whereas, aerosols collected outdoors tested negative in the last three kidding seasons. Viable C. burnetii was detectable in environmental dust collected inside the barn until the third kidding season following the outbreak. These results indicate that after an outbreak of Q fever, the risk of infection for humans and susceptible animals can remain high for at least three kidding seasons when the number of C. burnetii animal shedders is still high, even when bacterial excretion is low. IMPORTANCE: Q fever is a zoonosis distributed worldwide. Ruminants are the main reservoir, and infection can cause high rates of abortion. After entering a farm, Coxiella burnetii infection can persist in the animal population over several lambing/kidding periods. Once infection is established in a herd, vaccination with the inactivated Phase I vaccine significantly reduces bacterial shedding, but although at low levels, excretion may continue to occur for several lambing/kidding seasons. The time that C. burnetii remains viable in the farm environment after an outbreak of Q fever determines the period when risk of infection is high for the people in close contact. This work showed that this period extends at least three kidding seasons after the outbreak. These results provided valuable information on the epidemiology of C. burnetii infection in goat herds and may help to develop guidelines for controlling the disease and reducing infection risk for susceptible people and animals.

CD8+ T Cell-Dependent Antitumor Activity In Vivo of a Mass Spectrometry-Identified Neoepitope despite Undetectable CD8+ Immunogenicity In Vitro.

Identification of neoepitopes that can control tumor growth in vivo remains a challenge even 10 y after the first genomics-defined cancer neoepitopes were identified. In this study, we identify a neoepitope, resulting from a mutation in the junction plakoglobin (Jup) gene (chromosome 11), from the mouse colon cancer line MC38-FABF (C57BL/6). This neoepitope, Jup mutant (JupMUT), was detected during mass spectrometry of MHC class I-eluted peptides from the tumor. JupMUT has a predicted binding affinity of 564 nM for the Kb molecule and a higher predicted affinity of 82 nM for Db. However, whereas structural modeling of JupMUT and its unmutated counterpart Jup wild-type indicates that there are little conformational differences between the two epitopes bound to Db, large structural divergences are predicted between the two epitopes bound to Kb. Together with in vitro binding data with RMA-S cells, these data suggest that Kb rather than Db is the relevant MHC class I molecule of JupMUT. Immunization of naive C57BL/6 mice with JupMUT elicits CD8-dependent tumor control of a MC38-FABF challenge. Despite the CD8 dependence of JupMUT-mediated tumor control in vivo, CD8+ T cells from JupMUT-immunized mice do not produce higher levels of IFN-γ than do naive mice. The structural and immunological characteristics of JupMUT are substantially different from those of many other neoepitopes that have been shown to mediate tumor control.

A Q fever outbreak among visitors to a natural cave, Bizkaia, Spain, December 2020 to October 2021.

We describe a large Q fever outbreak reported in Spain, including 108 cases, 53 with pneumonia and 27 requiring hospitalisations. The first cases were detected in February 2021 among rock climbers visiting a cave in Bizkaia, and the last case was detected in October 2021. Most cases were notified after the Easter holiday (April-May 2021). More males (63.9%) than females (36.1%) were infected (median ages: 42 (1-68) and 39 years (6-61), respectively). We detected Coxiella burnetii by PCR in faecal, dust and/or aerosol samples taken inside the cave in March 2021, and in dust and aerosol samples collected between March 2021 and February 2023. Coxiella burnetii from dust samples were cultured on Vero cells, showing viability for 24 months. Based on serological and genotyping data, goats sheltering in the cave were the most likely source of infection. The cave was closed on 29 April 2021, movements of goats and sheep in the area were restricted (March-July 2021), and the animals were vaccinated in October 2021. Investigation of Q fever outbreaks requires a multidisciplinary One Health approach as these outbreaks can occur in unexpected places like natural sites where animals are present.

Dynamic model assuming mutually inhibitory biomarkers of frailty suggests bistability with contrasting mobility phenotypes.

Bistability is a fundamental biological phenomenon associated with "switch-like" behavior reflecting the capacity of a system to exist in either of two stable states. It plays a role in gene regulation, cell fate switch, signal transduction and cell oscillation, with relevance for cognition, hearing, vision, sleep, gait and voiding. Here we consider a potential role for bistability in the existence of specific frailty states or phenotypes as part of disablement pathways. We use mathematical modeling with two frailty biomarkers (insulin growth factor-1, IGF-1 and interleukin-6, IL-6), which mutually inhibit each other. In our model, we demonstrate that small variations around critical IGF-1 or IL-6 blood levels lead to strikingly different mobility outcomes. We employ deterministic modeling of mobility outcomes, calculating the average trends in population health. Our model predicts the bistability of clinical outcomes: the deterministically-computed likelihood of an individual remaining mobile, becoming less mobile, or dying over time either increases to almost 100% or decreases to almost zero. Contrary to statistical models that attempt to estimate the likelihood of final outcomes based on probabilities and correlations, our model predicts functional outcomes over time based on specific hypothesized molecular mechanisms. Instead of estimating probabilities based on stochastic distributions and arbitrary priors, we deterministically simulate model outcomes over a wide range of physiological parameter values within experimentally derived boundaries. Our study is "a proof of principle" as it is based on a major assumption about mutual inhibition of pathways that is oversimplified. However, by making such an assumption, interesting effects can be described qualitatively. As our understanding of molecular mechanisms involved in aging deepens, we believe that such modeling will not only lead to more accurate predictions, but also help move the field from using mostly studies of associations to mechanistically guided approaches.

GeNeo: A Bioinformatics Toolbox for Genomics-Guided Neoepitope Prediction.

High-throughput DNA and RNA sequencing are revolutionizing precision oncology, enabling personalized therapies such as cancer vaccines designed to target tumor-specific neoepitopes generated by somatic mutations expressed in cancer cells. Identification of these neoepitopes from next-generation sequencing data of clinical samples remains challenging and requires the use of complex bioinformatics pipelines. In this paper, we present GeNeo, a bioinformatics toolbox for genomics-guided neoepitope prediction. GeNeo includes a comprehensive set of tools for somatic variant calling and filtering, variant validation, and neoepitope prediction and filtering. For ease of use, GeNeo tools can be accessed via web-based interfaces deployed on a Galaxy portal publicly accessible at https://neo.engr.uconn.edu/. A virtual machine image for running GeNeo locally is also available to academic users upon request.

Synthesis and Characterization of Coordination Compound [Eu(µ2-OC2H5)(btfa)(NO3)(phen)]2phen with High Luminescence Efficiency.

A high-luminescent, blue-light excitable europium(III) coordination complex, [Eu(µ2-OC2H5)(btfa)(NO3)(phen)]2phen (1) {btfa = benzoyl trifluoroacetone, phen = 1,10-phenantroline}, has been synthesized and investigated. The complex was characterized by infrared (IR) and photoluminescence (PL) spectroscopy. The PL emission spectra of powder samples registered in a range of 10.7-300 K exhibit characteristic metal-centered luminescence bands, assigned to internal radiative transitions of the Eu3+ ion, 5D1→7Fj and 5D0→7Fj (j = 0-4). The high-resolution spectrum of the transition 5D0→7F0 shows that it consists of two narrow components, separated by 0.96 meV, which indicates the presence in the matrix of two different sites of the Eu3+ ion. The splitting pattern of 5D0→7Fj (j = 0-4) transitions indicates that europium ions are located in a low-symmetry environment. The absolute quantum yield and the sensitization efficiency were determined to be 49.2% and 89.3%, respectively. The complex can be excited with low-cost lasers at around 405 nm and is attractive for potential applications in optoelectronics and biochemistry.

Protocol of comparison of the effects of single plasma exchange and double filtration plasmapheresis on peripheral lymphocyte phenotypes in patients with Chronic Inflammatory Demyelinating Polyradiculoneuropathy: a monocentric prospective study with single-case experimental design.

BACKGROUND: Chronic Inflammatory Demyelinating Polyradiculoneuropathy (CIDP), a rare disorder affecting young adults, causes gradual weakness of the limbs, areflexia and impaired sensory function. New CIDP phenotypes without pathogenic antibodies but with modified cell profiles have been described. Treatments include corticotherapy, intravenous immunoglobulins, and plasmapheresis but the latter's action mechanisms remain unclear. Plasmapheresis supposedly removes toxic agents like antibodies from plasma but it is uncertain whether it has an immune-modulating effect. Also, the refining mechanisms of the two main plasmapheresis techniques-single plasma exchange and double filtration plasmapheresis (DFPP) - are different and unclear. This study aims to compare the evolution of peripheral lymphocyte profiles in patients with CIDP according to their treatment (single centrifugation plasmapheresis or DFPP) to better grasp the action mechanisms of both techniques. METHOD: In this proof-of-concept, monocentric, prospective, Single-Case Experimental Design study, 5 patients are evaluated by alternating their treatment type (single plasma exchange or DFPP) for 6 courses of treatment after randomization to their first treatment type. Each course of treatment lasts 2-4 weeks. For single plasma exchange, 60 ml/kg plasma will be removed from the patient and replaced with albumin solutes, with a centrifugation method to avoid the immunological reaction caused by the membrane used with the filtration method. For DFPP, 60 ml/kg plasma will be removed from the patient with a plasma separator membrane, then processed via a fractionator membrane to remove molecules of a greater size than albumin before returning it to the patient. This technique requires no substitution solutes, only 20 g of albumin to replace what would normally be lost during a session. The primary outcome is the difference between the two plasmapheresis techniques in the variation of the TH1/TH17 ratio over the period D0H0-D0H3 and D0H0-D7. Secondary outcomes include the variation in lymphocyte subpopulations at each session and between therapeutic plasmapheresis techniques, the clinical evolution, tolerance and cost of treatments. DISCUSSION: Understanding the action mechanisms of single plasma exchange and DFPP will help us to offer the right treatment to each patient with CIPD according to efficacy, tolerance and cost. TRIAL REGISTRATION: ClinicalTrials.gov under the no. NCT04742374 and date of registration 10 December 2020.

Stable prevalence of Coxiella burnetii in wildlife after a decade of surveillance in northern Spain.

Coxiella burnetii is an obligate intracellular zoonotic bacterium widespread in nature that causes Q fever in animals and humans. The most common sources of human infection are domestic ruminants, but wildlife can also act as reservoir. Here, spleen samples from 652 wild ungulates and 218 wild birds collected in 2011-2019 in the Basque Country (northern Spain) were analysed by real-time PCR (IS1111 gene) and the results compared with data from a past study in 2001-2006. Among wild ungulates, C. burnetii DNA was detected in 7.0% (6/86) of roe deer (Capreolus capreolus), 1.9% (9/484) of wild boar (Sus scrofa) and 2.4% (2/82) of red deer (Cervus elaphus). The prevalence in roe deer was significantly higher compared to wild boar (p = 0.006). Among wild birds, only one white stork (Ciconia ciconia) tested positive. SNP-typing of C. burnetii-positive samples showed that wild ungulates shared SNP 2, SNP 6 and SNP 8 genotypes with domestic ruminants of the region. However, the white stork harboured a C. burnetii genotype (SNP 3) never identified in the studied area before. Comparing these results with those obtained in the same area a decade before (2001-2006), no significant differences were observed in the prevalence of C. burnetii in any of the wildlife species, indicating stability in C. burnetii prevalence. Nevertheless, continuous surveillance is needed to monitor any future changes in the reservoir role of roe deer and wild boar considering the increase in density of both species observed in Europe in the last decades.

TNet: Transmission Network Inference Using Within-Host Strain Diversity and its Application to Geographical Tracking of COVID-19 Spread.

The inference of disease transmission networks is an important problem in epidemiology. One popular approach for building transmission networks is to reconstruct a phylogenetic tree using sequences from disease strains sampled from infected hosts and infer transmissions based on this tree. However, most existing phylogenetic approaches for transmission network inference are highly computationally intensive and cannot take within-host strain diversity into account. Here, we introduce a new phylogenetic approach for inferring transmission networks, TNet, that addresses these limitations. TNet uses multiple strain sequences from each sampled host to infer transmissions and is simpler and more accurate than existing approaches. Furthermore, TNet is highly scalable and able to distinguish between ambiguous and unambiguous transmission inferences. We evaluated TNet on a large collection of 560 simulated transmission networks of various sizes and diverse host, sequence, and transmission characteristics, as well as on 10 real transmission datasets with known transmission histories. Our results show that TNet outperforms two other recently developed methods, phyloscanner and SharpTNI, that also consider within-host strain diversity. We also applied TNet to a large collection of SARS-CoV-2 genomes sampled from infected individuals in many countries around the world, demonstrating how our inference framework can be adapted to accurately infer geographical transmission networks. TNet is freely available from https://compbio.engr.uconn.edu/software/TNet/.

Reversion analysis reveals the in vivo immunogenicity of a poorly MHC I-binding cancer neoepitope.

High-affinity MHC I-peptide interactions are considered essential for immunogenicity. However, some neo-epitopes with low affinity for MHC I have been reported to elicit CD8 T cell dependent tumor rejection in immunization-challenge studies. Here we show in a mouse model that a neo-epitope that poorly binds to MHC I is able to enhance the immunogenicity of a tumor in the absence of immunization. Fibrosarcoma cells with a naturally occurring mutation are edited to their wild type counterpart; the mutation is then re-introduced in order to obtain a cell line that is genetically identical to the wild type except for the neo-epitope-encoding mutation. Upon transplantation into syngeneic mice, all three cell lines form tumors that are infiltrated with activated T cells. However, lymphocytes from the two tumors that harbor the mutation show significantly stronger transcriptional signatures of cytotoxicity and TCR engagement, and induce greater breadth of TCR reactivity than those of the wild type tumors. Structural modeling of the neo-epitope peptide/MHC I pairs suggests increased hydrophobicity of the neo-epitope surface, consistent with higher TCR reactivity. These results confirm the in vivo immunogenicity of low affinity or 'non-binding' epitopes that do not follow the canonical concept of MHC I-peptide recognition.

Pipeline for Analyzing Activity of Metabolic Pathways in Planktonic Communities Using Metatranscriptomic Data.

In this article, we present our novel pipeline for analysis of metabolic activity using a microbial community's metatranscriptome sequence data set for validation. Our method is based on expectation-maximization (EM) algorithm and provides enzyme expression and pathway activity levels. Further expanding our analysis, we consider individual enzymatic activity and compute enzyme participation coefficients to approximate the metabolic pathway activity more accurately. We apply our EM pathways pipeline to a metatranscriptomic data set of a plankton community from surface waters of the Northern Gulf of Mexico. The data set consists of RNA-seq data and respective environmental parameters, which were sampled at two depths, six times a day over multiple 24-hour cycles. Furthermore, we discuss microbial dependence on day-night cycle within our findings based on a three-way correlation of the enzyme expression during antipodal times-midnight and noon. We show that the enzyme participation levels strongly affect the metabolic activity estimates: that is, marginal and multiple linear regression of enzymatic and metabolic pathway activity correlated significantly with the recorded environmental parameters. Our analysis statistically validates that EM-based methods produce meaningful results, as our method confirms statistically significant dependence of metabolic pathway activity on the environmental parameters, such as salinity, temperature, brightness, and a few others.

Analysis of environmental dust in goat and sheep farms to assess Coxiella burnetii infection in a Q fever endemic area: Geographical distribution, relationship with human cases and genotypes.

Real-time PCR analysis of environmental samples (dust and aerosols) is an easy tool to investigate the presence of Coxiella burnetii in the farm environment. The aim of this study was to assess the distribution of C. burnetii DNA in dust collected inside animal premises from 272 small ruminant farms in Bizkaia (northern Spain), a region with recent reports of human Q fever cases and outbreaks. Within each farm, 5 samples of dust were collected from difference surfaces, and data on animal census, management procedures, characteristics of the premises and geographic location were collected. Real-time PCR analysis of the dust samples detected presence of C. burnetii DNA in 98 farms (36.0%), flock-prevalence being higher in sheep (38.9%) or mixed ovine-caprine production systems (36.8%), compared to goats (25.0%). Larger bacterial burdens were observed in mixed farms, compared to sheep (p < .05). Single nucleotide polymorphism (SNP) analysis identified 5 different genotypes, with SNP8 being the predominant genotype (73%), followed by SNP6 (11%), SNP2 (9%), SNP4 (5%) and SNP1 (2%). Proportion of farms where C. burnetii DNA was detected differed among the different agricultural counties, and a higher proportion of C. burnetii DNA positive farms was associated with the occurrence of recent human Q fever outbreaks at several geographical locations. Dust sampling in domestic ruminant farms coupled with real-time PCR to screen for the presence of C. burnetii and estimate bacterial load can be a useful tool to identify herds and regions with high prevalence, define priority actions and monitor the effect of control measures. If combined with molecular genotyping and spatial distribution maps, it can help to identify farm contamination sources and trace the origin of human outbreaks.

SC1: A Tool for Interactive Web-Based Single-Cell RNA-Seq Data Analysis.

Single-cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. In this study, we present SC1 a web-based highly interactive scRNA-Seq data analysis tool publicly accessible at https://sc1.engr.uconn.edu. The tool presents an integrated workflow for scRNA-Seq analysis, implements a novel method of selecting informative genes based on term-frequency inverse-document-frequency scores, and provides a broad range of methods for clustering, differential expression analysis, gene enrichment, interactive visualization, and cell cycle analysis. The tool integrates other single-cell omics data modalities such as T-cell receptor (TCR)-Seq and supports several single-cell sequencing technologies. In just a few steps, researchers can generate a comprehensive analysis and gain powerful insights from their scRNA-Seq data.

RunBioSimulations: an extensible web application that simulates a wide range of computational modeling frameworks, algorithms, and formats.

Comprehensive, predictive computational models have significant potential for science, bioengineering, and medicine. One promising way to achieve more predictive models is to combine submodels of multiple subsystems. To capture the multiple scales of biology, these submodels will likely require multiple modeling frameworks and simulation algorithms. Several community resources are already available for working with many of these frameworks and algorithms. However, the variety and sheer number of these resources make it challenging to find and use appropriate tools for each model, especially for novice modelers and experimentalists. To make these resources easier to use, we developed RunBioSimulations (https://run.biosimulations.org), a single web application for executing a broad range of models. RunBioSimulations leverages community resources, including BioSimulators, a new open registry of simulation tools. These resources currently enable RunBioSimulations to execute nine frameworks and 44 algorithms, and they make RunBioSimulations extensible to additional frameworks and algorithms. RunBioSimulations also provides features for sharing simulations and interactively visualizing their results. We anticipate that RunBioSimulations will foster reproducibility, stimulate collaboration, and ultimately facilitate the creation of more predictive models.

Direct reprogramming of oligodendrocyte precursor cells into GABAergic inhibitory neurons by a single homeodomain transcription factor Dlx2.

Oligodendrocyte precursor cells (NG2 glia) are uniformly distributed proliferative cells in the mammalian central nervous system and generate myelinating oligodendrocytes throughout life. A subpopulation of OPCs in the neocortex arises from progenitor cells in the embryonic ganglionic eminences that also produce inhibitory neurons. The neuronal fate of some progenitor cells is sealed before birth as they become committed to the oligodendrocyte lineage, marked by sustained expression of the oligodendrocyte transcription factor Olig2, which represses the interneuron transcription factor Dlx2. Here we show that misexpression of Dlx2 alone in postnatal mouse OPCs caused them to switch their fate to GABAergic neurons within 2 days by downregulating Olig2 and upregulating a network of inhibitory neuron transcripts. After two weeks, some OPC-derived neurons generated trains of action potentials and formed clusters of GABAergic synaptic proteins. Our study revealed that the developmental molecular logic can be applied to promote neuronal reprogramming from OPCs.

Distribution of Triclocarban in Natural Aqueous Systems Amended with Carbon Nanomaterials.

In this work, the sorption of TCC in natural aqueous solutions with different chemical compositions, on amended sediments with carbon nanomaterials such as MWCNTs and C60, pristine and weathered is presented. The variation of the temperature, the composition of the natural water, the compositions of the sediment were studied, the results were correlated for a better understanding of the possible effects of the carbon nanomaterials in the environment.

An unbiased approach to defining bona fide cancer neoepitopes that elicit immune-mediated cancer rejection.

Identification of neoepitopes that are effective in cancer therapy is a major challenge in creating cancer vaccines. Here, using an entirely unbiased approach, we queried all possible neoepitopes in a mouse cancer model and asked which of those are effective in mediating tumor rejection and, independently, in eliciting a measurable CD8 response. This analysis uncovered a large trove of effective anticancer neoepitopes that have strikingly different properties from conventional epitopes and suggested an algorithm to predict them. It also revealed that our current methods of prediction discard the overwhelming majority of true anticancer neoepitopes. These results from a single mouse model were validated in another antigenically distinct mouse cancer model and are consistent with data reported in human studies. Structural modeling showed how the MHC I-presented neoepitopes had an altered conformation, higher stability, or increased exposure to T cell receptors as compared with the unmutated counterparts. T cells elicited by the active neoepitopes identified here demonstrated a stem-like early dysfunctional phenotype associated with effective responses against viruses and tumors of transgenic mice. These abundant anticancer neoepitopes, which have not been tested in human studies thus far, can be exploited for generation of personalized human cancer vaccines.

Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.

BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a small proportion of the neoepitopes generated by somatic DNA mutations in cancer cells lead to tumor rejection. Since it is impractical to experimentally assess all candidate neoepitopes prior to vaccination, developing accurate methods for predicting tumor-rejection mediating neoepitopes (TRMNs) is critical for enabling routine clinical use of cancer vaccines. RESULTS: In this paper we introduce Positive-unlabeled Learning using AuTOml (PLATO), a general semi-supervised approach to improving accuracy of model-based classifiers. PLATO generates a set of high confidence positive calls by applying a stringent filter to model-based predictions, then rescores remaining candidates by using positive-unlabeled learning. To achieve robust performance on clinical samples with large patient-to-patient variation, PLATO further integrates AutoML hyper-parameter tuning, classification threshold selection based on spies, and support for bootstrapping. CONCLUSIONS: Experimental results on real datasets demonstrate that PLATO has improved performance compared to model-based approaches for two key steps in TRMN prediction, namely somatic variant calling from exome sequencing data and peptide identification from MS/MS data.