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At least 37 records · Page 2Linked to original sources

Identifying protein construct variants with increased crystallization propensity--a case study.

This study describes an efficient multiparallel automated workflow of cloning, expression, purification, and crystallization of a large set of construct variants for isolated protein domains aimed at structure determination by X-ray crystallography. This methodology is applied to MAPKAP kinase 2, a key enzyme in the inflammation pathway and thus an attractive drug target. The study reveals a distinct subset of truncation variants with improved crystallization properties. These constructs distinguish themselves by increased solubility and stability during a parallel automated multistep purification process including removal of the recombinant tag. High-throughput protein melting point analysis characterizes this subset of constructs as particularly thermostable. Both parallel purification screening and melting point determination clearly identify residue 364 as the optimal C terminus for the kinase domain. Moreover, all three constructs that ultimately crystallized feature this C terminus. At the N terminus, only three amino acids differentiate a noncrystallizing from a crystallizing construct. This study addresses the very common issues associated with difficult to crystallize proteins, those of solubility and stability, and the crucial importance of particular residues in the formation of crystal contacts. A methodology is suggested that includes biophysical measurements to efficiently identify and produce construct variants of isolated protein domains which exhibit higher crystallization propensity.

Cloning, Molecular↗

A liquid handling platform for standardized quantification of cell-free enzymatic activity encoded by antimicrobial resistance genes.

Antimicrobial resistance (AMR) is a growing global threat to human health, and rapid methods for characterizing emerging antimicrobial resistance genes (ARGs) are needed. Here, we develop a semi-automated workflow using cell-free gene expression systems to measure the activity of two ARGs encoded on plasmid DNA that produce rifampicin-inactivating and gentamicin-inactivating enzymes. We validated the use of a small benchtop Myra liquid handling system compared to manual pipetting, with no statistical differences observed. After optimizing the pre-incubation time of ARGs and dispensing protocol, expression of aac(3)-IIa increased the half-maximal inhibition concentration (IC50) of gentamicin by over 150-fold, whilst arr-3 increased the IC50 of rifampicin by ~20-fold compared to controls. This methodology for rapid, semi-automated ARG characterization offers a strategy to combat AMR by assessing novel ARGs identified through genomic surveillance or profiling activity of new or derivative antibiotics.

aminoglycoside resistance↗

Integration, acceptance testing, and clinical operation of the Medical Information, Communication and Archive System, phase II.

The Medical Information, Communication and Archive System (MICAS) is a multivendor incremental approach to picture archiving and communications system (PACS). It is a multimodality integrated image management system that is seamlessly integrated with the radiology information system (RIS). Phase II enhancements of MICAS include a permanent archive, automated workflow, study caches, Microsoft (Redmond, WA) Windows NT diagnostic workstations with all components adhering to Digital Information Communications in Medicine (DICOM) standards. MICAS is designed as an enterprise-wide PACS to provide images and reports throughout the Strong Health healthcare network. Phase II includes the addition of a Cemax-Icon (Fremont, CA) archive, PACS broker (Mitra, Waterloo, Canada), an interface (IDX PACSlink, Burlington, VT) to the RIS (IDXrad) plus the conversion of the UNIX-based redundant array of inexpensive disks (RAID) 5 temporary archives in phase I to NT-based RAID 0 DICOM modality-specific study caches (ImageLabs, Bedford, MA). The phase I acquisition engines and workflow management software was uninstalled and the Cemax archive manager (AM) assumed these functions. The existing ImageLabs UNIX-based viewing software was enhanced and converted to an NT-based DICOM viewer. Installation of phase II hardware and software and integration with existing components began in July 1998. Phase II of MICAS demonstrates that a multivendor open-system incremental approach to PACS is feasible, cost-effective, and has significant advantages over a single-vendor implementation.

Compact Disks↗

DeepPlaque: a scalable multimodal platform for Aβ pathology and cell analysis in Alzheimer's disease.

Histological analysis is essential for understanding disease pathology and the microenvironment, particularly in Alzheimer's disease (AD), characterized by beta-amyloid (Aβ) plaques that exist as diffuse, fibrillar, and core species, with distinct toxicity levels. However, accurate classification of Aβ plaque types in postmortem brain tissues and profiling of surrounding cells present significant challenges. To address these challenges, we developed "DeepPlaque", an integrated system featuring "PlaqueNet", a deep learning model for automated classification of Aβ plaque species from diverse imaging platforms. DeepPlaque includes automated workflows for cellular phenotyping and proteomic profiling through targeted laser microdissection. PlaqueNet achieves expert-level accuracy (AUC > 90%) in classifying the 3 major Aβ plaque species, supporting consistent and large-scale annotation. By integrating spatial cellular phenotyping with laser microdissection, DeepPlaque enables high-throughput proteomic analysis of Aβ plaque niches, revealing that microglia are more abundant around core and fibrillar Aβ plaques, with increased expression of apolipoprotein E and amyloid precursor protein in core Aβ plaques. This customizable platform enhances the molecular and cellular characterization of Aβ plaque-associated environments, providing critical insights into AD pathology.

Alzheimer Disease↗

A bioinformatics pipeline for high-throughput microbial multilocus sequence typing (MLST) analyses.

Multilocus sequence typing (MLST) analysis for semi-routine applications is hindered by the downstream, manually intensive steps of processing the raw sequence data files. This report describes the development of an MLST pipeline that automates DNA sequence editing and analysis in order to significantly reduce the time required for processing data. Validation using a pneumococcal dataset revealed complete agreement between the results generated by manual and automated workflows. The MLST pipeline was developed for both double-strand and single-strand sequencing.

Bacteria↗

Development of a Web-based event reporting system in an academic environment.

In pursuit of a strategy for patient safety and error reduction, The Ohio State University Health System developed and implemented a standardized voluntary event reporting system. The Web-based application is user friendly as well as context-sensitive and encompasses a broad range of errors, events, and near misses. A full organizational transformation was required to effectively implement the system, which involved process reengineering for event entry and for postentry automated workflows. This system serves as the foundation for efficient and consistent reporting processes, which are essential for encouraging a culture of commitment to patient safety.

Academic Medical Centers↗

Selective isolation of glycoproteins and glycopeptides for MALDI-TOF MS detection supported by magnetic particles.

Glycosylation is the most common form of posttranslational modification of proteins (50-80%). The isolation, discovery, and subsequent identification of glycosylated peptides and proteins is becoming more and more important in glycoproteomics and diagnosis. MALDI-TOF mass spectrometry is an ideal technique for identifying peptides and proteins and their corresponding modifications. The enrichment of glycosylated peptides and proteins from different sources can be attained by affinity chromatography supported by functionalized magnetic particles. Covalent coating of magnetic beads with Concanavalin A (ConA) and diboronic acid was performed by carbodiimide and poly-glutaraldehyde methods, respectively. The functionalized beads were employed to establish and optimize protocols for the binding and detection of glycosylated peptides and proteins with respect to an automated workflow and the subsequent detection and identification by MALDI-TOF mass spectrometry. For several model proteins, the capture and identification could be demonstrated by SDS-PAGE and MALDI-TOF mass spectrometry. According to the type of glycosylation (high man-nose, hybrid, or complex type) the different proteins were enriched by ConA or boronic acid-functionalized beads.

Animals↗

How automated access verification can help organizations demonstrate HIPAA compliance: A case study.

This case study of Sharp HealthCare takes an in depth look at how the organization has embedded security policies into its business process and automated workflow to ensure users are granted only the IT access that is necessary for them to perform their jobs and to ensure patient privacy Some of the most pressing audit and compliance concerns in healthcare organizations today revolve around the need to constantly review and give an account for users' IT access. The need for this at Sharp is exacerbated because of the high rate of change within the organization and the large percentage of non-employee staff such as traveling nurses moving throughout hospital departments on their rotations. By implementing a software solution to verify the accuracy of user access rights or automatically initiate appropriate corrective actions, Sharp is now able to extend the responsibility and accountability for compliance to the most appropriate resources.

Access to Information↗

A procedure for setting up high-throughput nanolitre crystallization experiments. Crystallization workflow for initial screening, automated storage, imaging and optimization.

Crystallization trials at the Division of Structural Biology in Oxford are now almost exclusively carried out using a high-throughput workflow implemented in the Oxford Protein Production Facility. Initial crystallization screening is based on nanolitre-scale sitting-drop vapour-diffusion experiments (typically 100 nl of protein plus 100 nl of reservoir solution per droplet) which use standard crystallization screening kits and 96-well crystallization plates. For 294 K crystallization trials the barcoded crystallization plates are entered into an automated storage system with a fully integrated imaging system. These plates are imaged in accordance with a pre-programmed schedule and the resulting digital data for each droplet are harvested into a laboratory information-management system (LIMS), scored by crystal recognition software and displayed for user analysis via a web-based interface. Currently, storage for trials at 277 K is not automated and for imaging the crystallization plates are fed by hand into an imaging system from which the data enter the LIMS. The workflow includes two procedures for nanolitre-scale optimization of crystallization conditions: (i) a protocol for variation of pH, reservoir dilution and protein:reservoir ratio and (ii) an additive screen. Experience based on 592 crystallization projects is reported.

Animals↗

Automated purification of recombinant proteins: combining high-throughput with high yield.

Protein crystallography, mapping protein interactions, and other functional genomic approaches require purifying many different proteins, each of sufficient yield and homogeneity, for subsequent high-throughput applications. To fill this requirement efficiently, there is a need to develop robust, automated, high-throughput protein expression, and purification processes. We developed and compared two alternative workflows for automated purification of recombinant proteins based on expression of bacterial genes in Escherichia coli (E. coli). The first is a filtration separation protocol in which proteins of interest are expressed in a large volume, 800 ml of E. coli cultures, then isolated by filtration purification using Ni-NTA-Agarose (Qiagen). The second is a smaller scale magnetic separation method in which proteins of interest are expressed in a small volume, 25 ml, of E. coli cultures then isolated using a 96-well purification system with MagneHis Ni2+ Agarose (Promega). Both workflows provided comparable average yields of proteins, about 8 microg of purified protein per optical density unit of bacterial culture measured at 600 nm. We discuss advantages and limitations of these automated workflows, which can provide proteins with more than 90% purity and yields in the range of 100 microg to 45 mg per purification run, as well as strategies for optimizing these protocols.

Bacterial Proteins↗

Automated QSPR through Competitive Workflow.

This paper describes a novel software architecture, Competitive Workflow, which implements workflow as a distributed and competitive multi-agent system. The implementation of a competitive workflow architecture designed to model important computer-aided molecular design workflows, the Discovery Bus, is described. QSPR modelling results for three example ADME datasets, for solubility, human plasma protein binding and P-glycoprotein substrates using an autonomous QSPR modelling workflow implemented on the Discovery Bus are presented. The autonomous QSPR system allows exhaustive exploration of descriptor and model space, automated model validation and continuous updating as new data and methods are made available. Prediction of properties of novel structures by an ensemble of models is also a feature of the system.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

Mass spectrometry-based ligand binding assays in biomedical research.

INTRODUCTION: Ligand binding assays combining immunoaffinity enrichment steps with mass spectrometry (MS) readout have gained attention as a highly specific and sensitive tool for protein quantification. These techniques typically combine enzymatic fragmentation of the sample or enriched protein with capture on the protein or peptide-level for quantification. Antibodies ensure specific target recognition, while MS offers quantitative accuracy with isotopically labeled internal standards. This dual approach supports a broad dynamic range, enabling protein measurements from picomolar to nanomolar levels. These methods have diverse applications, from quantifying signaling proteins in basic research to biomarker monitoring in clinical trials and analyzing the pharmacokinetics of therapeutic proteins. AREAS COVERED: This review delves into the diverse workflows of immunoaffinity-MS, shedding light on the innovative strategies employed, their practical applications, efficacy, and inherent limitations in the realm of protein quantification. EXPERT OPINION: Immunoaffinity-MS has transformed protein analysis, but widespread adoption is hindered by complex workflows, high instrument costs, and limited capture molecule availability. Efforts to enhance automation, standardize workflows, and advance technological innovation aim to overcome these barriers. Improvements in mass spectrometer sensitivity, advances in recombinant capture technologies, and support from public initiatives are poised to further improve the reliability and accessibility of this method.

Mass Spectrometry↗

Integrative evidence-knowledge marker selection enhances LLM-based cell type annotation in single-cell RNA-seq analysis.

BACKGROUND: Cell type annotation is essential for gaining biological insight from single-cell RNA sequencing data, yet manual labeling remains time-consuming and difficult to reproduce. Various computational approaches have been developed to automate this process, and recent studies suggest that large language models can infer cell types with promising accuracy in single-cell analysis. However, most workflows still rely on cluster-specific markers derived from gene expression alone or manual curation. As a result, marker selection can be sensitive to statistical criteria and dataset-dependent bias, which may lead to the selection of less informative genes or missing important markers, while providing limited biological context. RESULTS: To address this limitation, we introduce CELLIA, an LLM-based workflow for automated and robust cell type annotation. CELLIA employs an integrative evidence-knowledge marker selection strategy that combines statistical differential expression criteria with curated tissue-specific marker resources to identify informative marker genes. In benchmarking analyses of 102 cell types, this approach improved agreement with manual annotations. In addition, CELLIA achieved higher agreement in subtype-level analyses of closely related immune populations and was further evaluated in a non-immune stromal subtype setting, covering 25 cell types in total. CONCLUSION: By integrating evidence-knowledge from gene expression with curated biological prior knowledge, CELLIA provides a more stable marker selection and improves the reliability of LLM-cell type annotation.

Cell type annotation↗

Fedflow: cloud orchestration for federated learning with the FeatureCloud platform.

MOTIVATION: Federated learning (FL) enables collaborative model training on geographically distributed genomic and clinical datasets while complying with data privacy laws and regulatory constraints. FeatureCloud is an existing platform for FL that provides an accessible web-based interface and a large repository of implemented methods. However, due to its graphical interface, FeatureCloud requires manual interaction of all participants, limiting automation, iteration, and reproducibility. RESULTS: We introduce fedflow, a Python-based command-line tool for headless orchestration of FL tasks with FeatureCloud. This tool uses distributed computing resources such as virtual machines or cloud instances to automate such workflows. This allows for scalable federated computing either in local simulations or deployed in a trusted environment. Further, we demonstrate how fedflow can be used to integrate FeatureCloud in reproducible Snakemake workflows. For this, we reanalyse a metagenomic dataset with two federated algorithms and compare the results to the centralized approach with pooled data. Overall, fedflow enables automation of multi-client FL tasks, facilitates embedding of FeatureCloud in standard bioinformatics pipelines and thereby helps increase reproducibility. AVAILABILITY: Fedflow is open-source and available at https://github.com/W-L/fedflow.

Journal Article↗

Colora: a Snakemake workflow for complete chromosome-scale de novo genome assembly.

MOTIVATION: De novo assembly creates reference genomes that underpin many modern biodiversity and conservation studies. Large numbers of new genomes are being assembled by labs around the world. To avoid duplication of efforts and variable data quality, we desire a best-practice assembly process, implemented as an automated portable workflow. RESULTS: Here, we present Colora, a Snakemake workflow that produces chromosome-scale de novo primary or phased genome assemblies complete with organelles using Pacific Biosciences HiFi, Hi-C, and optionally Oxford Nanopore Technologies reads as input. Colora is a user-friendly, versatile, and reproducible pipeline that is ready to use by researchers looking for an automated way to obtain high-quality de novo genome assemblies. AVAILABILITY AND IMPLEMENTATION: The source code of Colora is available on GitHub (https://github.com/LiaOb21/colora) and has been deposited in Zenodo under DOI https://doi.org/10.5281/zenodo.13321576. Colora is also available at the Snakemake Workflow Catalog (https://snakemake.github.io/snakemake-workflow-catalog/? usage=LiaOb21%2Fcolora).

Software↗

The strategic and operational characteristics of a distributed phased archive for a multivendor incremental implementation of picture archiving and communications systems.

The long-term (10 years) multimodality distributed phased archive for the Medical Information, Communication and Archive System (MICAS) is being implemented in three phases. The selection process took approximately 10 months. Based on the mandatory archive attributes and desirable features, Cemax-Icon (Fremont, CA) was selected as the vendor. The archive provides for an open-solution allowing incorporation of leading edge, "best of breed" hardware and software and provides maximum flexibility and automation of workflow both within and outside of radiology. The solution selected is media-independent, provides expandable storage capacity, and will provide redundancy and fault tolerance in phase II at minimum cost. Other attributes of the archive include scalable archive strategy, virtual image database with global query, and an object-oriented database. The archive is seamlessly integrated with the radiology information system (RIS) and provides automated fetching and routing, automated study reconciliation using modality worklist manager, clinical reports available at any Digital Imaging and Communications in Medicine (DICOM) workstation, and studies available for interpretation whether validated or not. Within 24 hours after a new study is acquired, four copies will reside within different components of the archive including a copy that can be stored off-site. Phase II of the archive will be installed during 1999 and will include a second Cemax-Icon archive and database using archive manager (AM) Version 4.0 in a second computer room.

Computer Communication Networks↗

Tractor workflow: a scalable Nextflow framework for local ancestry-aware genome-wide association studies.

MOTIVATION: The routine exclusion of admixed individuals from traditional genome-wide association studies (GWAS) due to concerns about spurious associations has limited multi-ancestry genetic discovery. Tractor addresses this issue by incorporating local ancestry into association testing, enabling the identification of ancestry-enriched signals and generating ancestry-specific summary statistics. However, adoption has been constrained by the complexity of prerequisite steps, including phasing and local ancestry inference, which require substantial bioinformatics expertise and introduce key analytical decision points. RESULTS: We developed a scalable, automated Nextflow workflow that integrates phasing, local ancestry inference, and Tractor association testing into a reproducible end-to-end pipeline. To demonstrate its utility, we applied the workflow to 32 blood biomarkers in 6245 two-way African-European admixed individuals from the UK Biobank. This pipeline performed efficiently at scale, replicating known associations and uncovering key ancestry-specific loci. These associations were largely driven by variants present on African ancestral tracts but absent from European tracts, underscoring the value of local ancestry-aware methods in uncovering previously masked genetic signals. AVAILABILITY AND IMPLEMENTATION: The workflow is modular, customizable, and compatible with commonly used phasing and local ancestry tools, minimizing manual intervention while preserving analytical flexibility. By lowering technical barriers to implementation, this framework facilitates broader adoption of local ancestry-aware GWAS, paving the way for expanded genetic discovery.

Humans↗