Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys.

Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensing solutions for wildlife population monitoring. To support in-flight orthorectification and machine learning processing to detect and classify wildlife from imagery in near real-time, we evaluated deep learning methods that address hardware limitations and the need for processing efficiencies to support the envisioned in-flight workflow. We developed an annotated dataset for a suite of marine birds from high-resolution digital aerial imagery collected over open water environments to train the models. The proposed 3-stage workflow for automated, in-flight data processing includes: 1) image filtering based on the probability of any bird occurrence, 2) bird instance detection, and 3) bird instance classification. For image filtering, we compared the performance of a binary classifier with Mask Region-based Convolutional Neural Network (Mask R-CNN) as a means of sub-setting large volumes of imagery based on the probability of at least one bird occurrence in an image. On both the validation and test datasets, the binary classifier achieved higher performance than Mask R-CNN for predicting bird occurrence at the image-level. We recommend the binary classifier over Mask R-CNN for workflow first-stage filtering. For bird instance detection, we leveraged Mask R-CNN as our detection framework and proposed an iterative refinement method to bootstrap our predicted detections from loose ground-truth annotations. We also discuss future work to address the taxonomic classification phase of the envisioned workflow.

Evaluation of Cellular Immune Response to Adeno-Associated Virus-Based Gene Therapy.

The number of approved or investigational late phase viral vector gene therapies (GTx) has been rapidly growing. The adeno-associated virus vector (AAV) technology continues to be the most used GTx platform of choice. The presence of pre-existing anti-AAV immunity has been firmly established and is broadly viewed as a potential deterrent for successful AAV transduction with a possibility of negative impact on clinical efficacy and a connection to adverse events. Recommendations for the evaluation of humoral, including neutralizing and total antibody based, anti-AAV immune response have been presented elsewhere. This manuscript aims to cover considerations related to the assessment of anti-AAV cellular immune response, including review of correlations between humoral and cellular responses, potential value of cellular immunogenicity assessment, and commonly used analytical methodologies and parameters critical for monitoring assay performance. This manuscript was authored by a group of scientists involved in GTx development who represent several pharma and contract research organizations. It is our intent to provide recommendations and guidance to the industry sponsors, academic laboratories, and regulatory agencies working on AAV-based GTx viral vector modalities with the goal of achieving a more consistent approach to anti-AAV cellular immune response assessment.

Evaluation of the Humoral Response to Adeno-Associated Virus-Based Gene Therapy Modalities Using Total Antibody Assays.

The number of viral vector-based gene therapies (GTx) continues to grow with two products (Zolgensma® and Luxturna®) approved in the USA as of March 2021. To date, the most commonly used vectors are adeno-associated virus-based (AAV). The pre-existing humoral immunity against AAV (anti-AAV antibodies) has been well described and is expected as a consequence of prior AAV exposure. Anti-AAV antibodies may present an immune barrier to successful AAV transduction and hence negatively impact clinical efficacy and may also result in adverse events (AEs) due to the formation of large immune complexes. Patients may be screened for the presence of anti-AAV antibodies, including neutralizing (NAb) and total binding antibodies (TAb) prior to treatment with the GTx. Recommendations for the development and validation of anti-AAV NAb detection methods have been presented elsewhere. This manuscript covers considerations related to anti-AAV TAb-detecting protocols, including the advantages of the use of TAb methods, selection of assay controls and reagents, and parameters critical to monitoring assay performance. This manuscript was authored by a group of scientists involved in GTx development representing eleven organizations. It is our intent to provide recommendations and guidance to industry sponsors, academic laboratories, and regulatory agencies working on AAV-based GTx viral vector modalities with the goal of achieving a more consistent approach to anti-AAV TAb assessment. Graphical abstract.

The MG-RAST API explorer: an on-ramp for RESTful query composition.

BACKGROUND: The MG-RAST API provides search capabilities and delivers organism and function data as well as raw or annotated sequence data via the web interface and its RESTful API. For casual users, however, RESTful APIs are hard to learn and work with. RESULTS: We created the graphical MG-RAST API explorer to help researchers more easily build and export API queries; understand the data abstractions and indices available in MG-RAST; and use the results presented in-browser for exploration, development, and debugging. CONCLUSIONS: The API explorer lowers the barrier to entry for occasional or first-time MG-RAST API users.

GCC Consolidated Feedback to ICH on the 2019 ICH M10 Bioanalytical Method Validation Draft Guideline.

The 13th GCC Closed Forum for Bioanalysis was held in New Orleans, Louisiana, USA on April 5th, 2019. This GCC meeting was organized to discuss the contents of the 2019 ICH M10 Bioanalytical Method Validation Draft Guideline published in February 2019 and consolidate the feedback of the GCC members. In attendance were 63 senior-level participants from eight countries representing 44 bioanalytical CRO companies/sites. This event represented a unique opportunity for CRO bioanalytical experts to share their opinions and concerns regarding the ICH M10 Bioanalytical Method Validation Draft Guideline and to build unified comments to be provided to the ICH.

MG-RAST version 4-lessons learned from a decade of low-budget ultra-high-throughput metagenome analysis.

As technologies change, MG-RAST is adapting. Newly available software is being included to improve accuracy and performance. As a computational service constantly running large volume scientific workflows, MG-RAST is the right location to perform benchmarking and implement algorithmic or platform improvements, in many cases involving trade-offs between specificity, sensitivity and run-time cost. The work in [Glass EM, Dribinsky Y, Yilmaz P, et al. ISME J 2014;8:1-3] is an example; we use existing well-studied data sets as gold standards representing different environments and different technologies to evaluate any changes to the pipeline. Currently, we use well-understood data sets in MG-RAST as platform for benchmarking. The use of artificial data sets for pipeline performance optimization has not added value, as these data sets are not presenting the same challenges as real-world data sets. In addition, the MG-RAST team welcomes suggestions for improvements of the workflow. We are currently working on versions 4.02 and 4.1, both of which contain significant input from the community and our partners that will enable double barcoding, stronger inferences supported by longer-read technologies, and will increase throughput while maintaining sensitivity by using Diamond and SortMeRNA. On the technical platform side, the MG-RAST team intends to support the Common Workflow Language as a standard to specify bioinformatics workflows, both to facilitate development and efficient high-performance implementation of the community's data analysis tasks.

Patterns of mercury and selenium exposure in minnesota common loons.

Common loons (Gavia immer) are at risk of elevated dietary mercury (Hg) exposure in portions of their breeding range. To assess the level of risk among loons in Minnesota (USA), we investigated loon blood Hg concentrations in breeding lakes across Minnesota. Loon blood Hg concentrations were regressed on predicted Hg concentrations in standardized 12-cm whole-organism yellow perch (Perca flavescens), based on fish Hg records from Minnesota lakes, using the US Geological Survey National Descriptive Model for Mercury in Fish. A linear model, incorporating common loon sex, age, body mass, and log-transformed standardized perch Hg concentration representative of each study lake, was associated with 83% of the variability in observed common loon blood Hg concentrations. Loon blood Hg concentration was positively related to standardized perch Hg concentrations; juvenile loons had lower blood Hg concentrations than adult females, and blood Hg concentrations of juveniles increased with body mass. Blood Hg concentrations of all adult common loons and associated standardized prey Hg for all loon capture lakes included in the study were well below proposed thresholds for adverse effects on loon behavior, physiology, survival, and reproductive success. The fish Hg modeling approach provided insights into spatial patterns of dietary Hg exposure risk to common loons across Minnesota. We also determined that loon blood selenium (Se) concentrations were positively correlated with Hg concentration. Average common loon blood Se concentrations exceeded the published provisional threshold. Environ Toxicol Chem 2019;38:524-532. Published 2018 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

The MG-RAST metagenomics database and portal in 2015.

MG-RAST (http://metagenomics.anl.gov) is an open-submission data portal for processing, analyzing, sharing and disseminating metagenomic datasets. The system currently hosts over 200,000 datasets and is continuously updated. The volume of submissions has increased 4-fold over the past 24 months, now averaging 4 terabasepairs per month. In addition to several new features, we report changes to the analysis workflow and the technologies used to scale the pipeline up to the required throughput levels. To show possible uses for the data from MG-RAST, we present several examples integrating data and analyses from MG-RAST into popular third-party analysis tools or sequence alignment tools.

A RESTful API for accessing microbial community data for MG-RAST.

Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, MG-RAST has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis, such as comparative analysis between multiple data sets. Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have greatly expanded access to MG-RAST data, as well as provided a mechanism for the use of third-party analysis tools with MG-RAST data. This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects. As part of the DOE Systems Biology Knowledgebase project (KBase, http://kbase.us) we have implemented a web services API for MG-RAST. This API complements the existing MG-RAST web interface and constitutes the basis of KBase's microbial community capabilities. In addition, the API exposes a comprehensive collection of data to programmers. This API, which uses a RESTful (Representational State Transfer) implementation, is compatible with most programming environments and should be easy to use for end users and third parties. It provides comprehensive access to sequence data, quality control results, annotations, and many other data types. Where feasible, we have used standards to expose data and metadata. Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users. We present an API that exposes the data in MG-RAST for consumption by our users, greatly enhancing the utility of the MG-RAST service.

Novel human radiation exposure biomarker panel applicable for population triage.

PURPOSE: To identify a panel of radiation-responsive plasma proteins that could be used in a point-of-care biologic dosimeter to detect clinically significant levels of ionizing radiation exposure. METHODS AND MATERIALS: Patients undergoing preparation for hematopoietic cell transplantation using radiation therapy (RT) with either total lymphoid irradiation or fractionated total body irradiation were eligible. Plasma was examined from patients with potentially confounding conditions and from normal individuals. Each plasma sample was analyzed for a panel of 17 proteins before RT was begun and at several time points after RT exposure. Paired and unpaired t tests between the dose and control groups were performed. Conditional inference trees were constructed based on panels of proteins to compare the non-RT group with the RT group. RESULTS: A total of 151 patients (62 RT, 41 infection, 48 trauma) were enrolled on the study, and the plasma from an additional 24 healthy control individuals was analyzed. In comparison with to control individuals, tenascin-C was upregulated and clusterin was downregulated in patients receiving RT. Salivary amylase was strongly radiation responsive, with upregulation in total body irradiation patients and slight downregulation in total lymphoid irradiation patients compared with control individuals. A panel consisting of these 3 proteins accurately distinguished between irradiated patients and healthy control individuals within 3 days after exposure: 97% accuracy, 0.5% false negative rate, 2% false positive rate. The accuracy was diminished when patients with trauma, infection, or both were included (accuracy, 74%-84%; false positive rate, 14%-33%, false negative rate: 8%-40%). CONCLUSIONS: A panel of 3 proteins accurately distinguishes unirradiated healthy donors from those exposed to RT (0.8-9.6 Gy) within 3 days of exposure. These findings have significant implications in terms of triaging individuals in the case of nuclear or other radiologic events.

Metazen - metadata capture for metagenomes.

BACKGROUND: As the impact and prevalence of large-scale metagenomic surveys grow, so does the acute need for more complete and standards compliant metadata. Metadata (data describing data) provides an essential complement to experimental data, helping to answer questions about its source, mode of collection, and reliability. Metadata collection and interpretation have become vital to the genomics and metagenomics communities, but considerable challenges remain, including exchange, curation, and distribution. Currently, tools are available for capturing basic field metadata during sampling, and for storing, updating and viewing it. Unfortunately, these tools are not specifically designed for metagenomic surveys; in particular, they lack the appropriate metadata collection templates, a centralized storage repository, and a unique ID linking system that can be used to easily port complete and compatible metagenomic metadata into widely used assembly and sequence analysis tools. RESULTS: Metazen was developed as a comprehensive framework designed to enable metadata capture for metagenomic sequencing projects. Specifically, Metazen provides a rapid, easy-to-use portal to encourage early deposition of project and sample metadata. CONCLUSIONS: Metazen is an interactive tool that aids users in recording their metadata in a complete and valid format. A defined set of mandatory fields captures vital information, while the option to add fields provides flexibility.

A metagenomics portal for a democratized sequencing world.

The democratized world of sequencing is leading to numerous data analysis challenges; MG-RAST addresses many of these challenges for diverse datasets, including amplicon datasets, shotgun metagenomes, and metatranscriptomes. The changes from version 2 to version 3 include the addition of a dedicated gene calling stage using FragGenescan, clustering of predicted proteins at 90% identity, and the use of BLAT for the computation of similarities. Together with changes in the underlying software infrastructure, this has enabled the dramatic scaling up of pipeline throughput while remaining on a limited hardware budget. The Web-based service allows upload, fully automated analysis, and visualization of results. As a result of the plummeting cost of sequencing and the readily available analytical power of MG-RAST, over 78,000 metagenomic datasets have been analyzed, with over 12,000 of them publicly available in MG-RAST.

A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE.

We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as "noise" or "error") within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms.

The M5nr: a novel non-redundant database containing protein sequences and annotations from multiple sources and associated tools.

BACKGROUND: Computing of sequence similarity results is becoming a limiting factor in metagenome analysis. Sequence similarity search results encoded in an open, exchangeable format have the potential to limit the needs for computational reanalysis of these data sets. A prerequisite for sharing of similarity results is a common reference. DESCRIPTION: We introduce a mechanism for automatically maintaining a comprehensive, non-redundant protein database and for creating a quarterly release of this resource. In addition, we present tools for translating similarity searches into many annotation namespaces, e.g. KEGG or NCBI's GenBank. CONCLUSIONS: The data and tools we present allow the creation of multiple result sets using a single computation, permitting computational results to be shared between groups for large sequence data sets.

Increased CCL2 expression and macrophage/monocyte migration during microbicide-induced vaginal irritation.

Despite availability of successful prevention strategies, HIV continues to spread at alarming rates, especially among women in developing countries. Vaginal microbicides offer a promising approach for blocking transmission of HIV when condom use cannot be negotiated with male partners. A major problem in the development of vaginal microbicides is chemically induced vaginal irritation, which can enhance the risk of HIV transmission. Evaluation of vaginal irritation prior to clinical trials typically uses an expensive and animal-intensive rabbit vaginal irritation model, which could be supplemented by measuring additional inflammatory biomarkers. We studied several immunological parameters as potential biomarkers of vaginal irritation, using the spermicides nonoxynol-9 and benzalkonium chloride as test microbicides. We measured amounts of cytokines, as well as inflammatory cells, in vaginal tissue lysates and on the vaginal surface. We observed that treatment with the selected microbicides increases quantities of the inflammatory cytokines interleukin-1beta, CXCL8, and CCL2 in the vaginal tissue parenchyma, and of CCL2 on the vaginal surface. This observation was correlated with increases in macrophages in the vaginal parenchyma. We suggest that measurements of CCL2 and macrophages can serve as new inflammatory biomarkers to evaluate the safety of promising novel microbicides for prevention of HIV.

The malaria secretome: from algorithms to essential function in blood stage infection.

The malaria agent Plasmodium falciparum is predicted to export a "secretome" of several hundred proteins to remodel the host erythrocyte. Prediction of protein export is based on the presence of an ER-type signal sequence and a downstream Host-Targeting (HT) motif (which is similar to, but distinct from, the closely related Plasmodium Export Element [PEXEL]). Previous attempts to determine the entire secretome, using either the HT-motif or the PEXEL, have yielded large sets of proteins, which have not been comprehensively tested. We present here an expanded secretome that is optimized for both P. falciparum signal sequences and the HT-motif. From the most conservative of these three secretome predictions, we identify 11 proteins that are preserved across human- and rodent-infecting Plasmodium species. The conservation of these proteins likely indicates that they perform important functions in the interaction with and remodeling of the host erythrocyte important for all Plasmodium parasites. Using the piggyBac transposition system, we validate their export and find a positive prediction rate of approximately 70%. Even for proteins identified by all secretomes, the positive prediction rate is not likely to exceed approximately 75%. Attempted deletions of the genes encoding the conserved exported proteins were not successful, but additional functional analyses revealed the first conserved secretome function. This gave new insight into mechanisms for the assembly of the parasite-induced tubovesicular network needed for import of nutrients into the infected erythrocyte. Thus, genomic screens combined with functional assays provide unexpected and fundamental insights into host remodeling by this major human pathogen.

Erythrocyte G protein as a novel target for malarial chemotherapy.

BACKGROUND: Malaria remains a serious health problem because resistance develops to all currently used drugs when their parasite targets mutate. Novel antimalarial drug targets are urgently needed to reduce global morbidity and mortality. Our prior results suggested that inhibiting erythrocyte Gs signaling blocked invasion by the human malaria parasite Plasmodium falciparum. METHODS AND FINDINGS: We investigated the erythrocyte guanine nucleotide regulatory protein Gs as a novel antimalarial target. Erythrocyte "ghosts" loaded with a Gs peptide designed to block Gs interaction with its receptors, were blocked in beta-adrenergic agonist-induced signaling. This finding directly demonstrates that erythrocyte Gs is functional and that propranolol, an antagonist of G protein-coupled beta-adrenergic receptors, dampens Gs activity in erythrocytes. We subsequently used the ghost system to directly link inhibition of host Gs to parasite entry. In addition, we discovered that ghosts loaded with the peptide were inhibited in intracellular parasite maturation. Propranolol also inhibited blood-stage parasite growth, as did other beta2-antagonists. beta-blocker growth inhibition appeared to be due to delay in the terminal schizont stage. When used in combination with existing antimalarials in cell culture, propranolol reduced the 50% and 90% inhibitory concentrations for existing drugs against P. falciparum by 5- to 10-fold and was also effective in reducing drug dose in animal models of infection. CONCLUSIONS: Together these data establish that, in addition to invasion, erythrocyte G protein signaling is needed for intracellular parasite proliferation and thus may present a novel antimalarial target. The results provide proof of the concept that erythrocyte Gs antagonism offers a novel strategy to fight infection and that it has potential to be used to develop combination therapies with existing antimalarials.

Lipid rafts and malaria parasite infection of erythrocytes.

Infection of human erythrocytes by the malarial parasite, Plasmodium falciparum, results in complex membrane sorting and signaling events in the mature erythrocyte. These events appear to rely heavily on proteins resident in erythrocyte lipid rafts. Over the past five years, we and others have undertaken a comprehensive characterization of major proteins present in erythrocyte detergent-resistant membrane lipid rafts and determined which of these proteins traffic to the host-derived membrane that bounds the intraerythrocytic parasite. The data suggest that raft association is necessary but not sufficient for vacuolar recruitment, and that there is likely a mechanism of active uptake of a subset of erythrocyte detergent-resistant membrane proteins. Of the ten internalized proteins, few have been evaluated for a role in malarial entry. The beta(2)-adrenergic receptor and heterotrimeric G protein G(s) signaling pathway proteins regulate invasion. The implications of these differences are discussed. In addition, the latter finding indicates that erythrocytes possess important signaling pathways. These signaling cascades may have important influences on in vivo malarial infection, as well as on erythrocyte membrane flexibility and adhesiveness in sickle cell anemia. With respect to malarial infection, host signaling components alone are not sufficient to induce formation of the malarial vacuole. Parasite proteins are likely to have a major role in making the intraerythrocytic environment conducive for vacuole formation. Such interactions should be the focus of future efforts to understand malarial infection of erythrocytes since host- and parasite-targeted interventions are urgently needed to combat this terrible disease.

A host-targeting signal in virulence proteins reveals a secretome in malarial infection.

Malaria parasites secrete proteins across the vacuolar membrane into the erythrocyte, inducing modifications linked to disease and parasite survival. We identified an 11-amino acid signal required for the secretion of proteins from the Plasmodium falciparum vacuole to the human erythrocyte. Bioinformatics predicted a secretome of >320 proteins and conservation of the signal across parasite species. Functional studies indicated the predictive value of the signal and its role in targeting virulence proteins to the erythrocyte and implicated its recognition by a receptor/transporter. Erythrocyte modification by the parasite may involve plasmodial heat shock proteins and be vastly more complex than hitherto realized.

Erythrocyte detergent-resistant membrane proteins: their characterization and selective uptake during malarial infection.

Infection of human erythrocytes by the apicomplexan malaria parasite Plasmodium falciparum results in endovacuolar uptake of 4 host proteins that reside in erythrocyte detergent-resistant membranes (DRMs). Whether this vacuolar transport reflects selective uptake of host DRM proteins remains unknown. A further complication is that DRMs of vastly different protein and cholesterol contents have been isolated from erythrocytes. Here we show that isolated DRMs containing the highest cholesterol-to-protein ratio have low protein mass. Liquid chromatography, mass spectrometry, and antibody-based studies reveal that the major DRM proteins are band 3, flotillin-1 and -2, peroxiredoxin-2, and stomatin. Band 3 and stomatin, which reflect the bulk mass of erythrocyte DRM proteins, and all tested non-DRM proteins are excluded from the vacuolar parasite. In contrast, flotillin-1 and -2 and 8 minor DRM proteins are recruited to the vacuole. These data suggest that DRM association is necessary but not sufficient for vacuolar recruitment and there is active, vacuolar uptake of a subset of host DRM proteins. Finally, the 10 internalized DRM proteins show varied lipid and peptidic anchors indicating that, contrary to the prevailing model of apicomplexan vacuole formation, DRM association, rather than lipid anchors, provides the preferred criteria for protein recruitment to the malarial vacuole.