A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease.

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant [to generate peptide-spectral matches (PSMs) and quantification], PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies. IMPORTANCE: Clinical metaproteomics has immense potential to offer functional insights into the microbiome and its contributions to human disease. However, there are numerous challenges in the metaproteomic analysis of clinical samples, including handling of very large protein sequence databases for sensitive and accurate peptide and protein identification from mass spectrometry data, as well as taxonomic and functional annotation of quantified peptides and proteins to enable interpretation of results. To address these challenges, we have developed a novel clinical metaproteomics workflow that provides customized bioinformatic identification, verification, quantification, and taxonomic and functional annotation. This bioinformatic workflow is implemented in the Galaxy ecosystem and has been used to characterize diverse clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness and availability for use by the research community via analysis of residual fluid from cervical swabs.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease.

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification and prioritization of microbial and host proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), and Unipept and MSstatsTMT (for taxonomy and functional annotation). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

Two structurally defined Aß polymorphs promote different pathological changes in susceptible mice.

Misfolded Aß is involved in the progression of Alzheimer's disease (AD). However, the role of its polymorphic variants or conformational strains in AD pathogenesis is not fully understood. Here, we study the seeding properties of two structurally defined synthetic misfolded Aß strains (termed 2F and 3F) using in vitro and in vivo assays. We show that 2F and 3F strains differ in their biochemical properties, including resistance to proteolysis, binding to strain-specific dyes, and in vitro seeding. Injection of these strains into a transgenic mouse model produces different pathological features, namely different rates of aggregation, formation of different plaque types, tropism to specific brain regions, differential recruitment of Aß40 /Aß42 peptides, and induction of microglial and astroglial responses. Importantly, the aggregates induced by 2F and 3F are structurally different as determined by ssNMR. Our study analyzes the biological properties of purified Aß polymorphs that have been characterized at the atomic resolution level and provides relevant information on the pathological significance of misfolded Aß strains.

A 3D Bioprinted In Vitro Model of Pulmonary Artery Atresia to Evaluate Endothelial Cell Response to Microenvironment.

Vascular atresia are often treated via transcatheter recanalization or surgical vascular anastomosis due to congenital malformations or coronary occlusions. The cellular response to vascular anastomosis or recanalization is, however, largely unknown and current techniques rely on restoration rather than optimization of flow into the atretic arteries. An improved understanding of cellular response post anastomosis may result in reduced restenosis. Here, an in vitro platform is used to model anastomosis in pulmonary arteries (PAs) and for procedural planning to reduce vascular restenosis. Bifurcated PAs are bioprinted within 3D hydrogel constructs to simulate a reestablished intervascular connection. The PA models are seeded with human endothelial cells and perfused at physiological flow rate to form endothelium. Particle image velocimetry and computational fluid dynamics modeling show close agreement in quantifying flow velocity and wall shear stress within the bioprinted arteries. These data are used to identify regions with greatest levels of shear stress alterations, prone to stenosis. Vascular geometry and flow hemodynamics significantly affect endothelial cell viability, proliferation, alignment, microcapillary formation, and metabolic bioprofiles. These integrated in vitro-in silico methods establish a unique platform to study complex cardiovascular diseases and can lead to direct clinical improvements in surgical planning for diseases of disturbed flow.

Patient-Specific 3D Bioprinted Models of Developing Human Heart.

The heart is the first organ to develop in the human embryo through a series of complex chronological processes, many of which critically rely on the interplay between cells and the dynamic microenvironment. Tight spatiotemporal regulation of these interactions is key in heart development and diseases. Due to suboptimal experimental models, however, little is known about the role of microenvironmental cues in the heart development. This study investigates the use of 3D bioprinting and perfusion bioreactor technologies to create bioartificial constructs that can serve as high-fidelity models of the developing human heart. Bioprinted hydrogel-based, anatomically accurate models of the human embryonic heart tube (e-HT, day 22) and fetal left ventricle (f-LV, week 33) are perfused and analyzed both computationally and experimentally using ultrasound and magnetic resonance imaging. Results demonstrate comparable flow hemodynamic patterns within the 3D space. We demonstrate endothelial cell growth and function within the bioprinted e-HT and f-LV constructs, which varied significantly in varying cardiac geometries and flow. This study introduces the first generation of anatomically accurate, 3D functional models of developing human heart. This platform enables precise tuning of microenvironmental factors, such as flow and geometry, thus allowing the study of normal developmental processes and underlying diseases.

Patient-Specific 3-Dimensional-Bioprinted Model for In Vitro Analysis and Treatment Planning of Pulmonary Artery Atresia in Tetralogy of Fallot and Major Aortopulmonary Collateral Arteries.

Background Tetralogy of Fallot with major aortopulmonary collateral arteries is a heterogeneous form of pulmonary artery (PA) stenosis that requires multiple forms of intervention. We present a patient-specific in vitro platform capable of sustained flow that can be used to train proceduralists and surgical teams in current interventions, as well as in developing novel therapeutic approaches to treat various vascular anomalies. Our objective is to develop an in vitro model of PA stenosis based on patient data that can be used as an in vitro phantom to model cardiovascular disease and explore potential interventions. Methods and Results From patient-specific scans obtained via computer tomography or 3-dimensional (3D) rotational angiography, we generated digital 3D models of the arteries. Subsequently, in vitro models of tetralogy of Fallot with major aortopulmonary collateral arteries were first 3D printed using biocompatible resins and next bioprinted using gelatin methacrylate hydrogel to simulate neonatal vasculature or second-order branches of an older patient with tetralogy of Fallot with major aortopulmonary collateral arteries. Printed models were used to study creation of extraluminal connection between an atretic PA and a major aortopulmonary collateral artery using a catheter-based interventional method. Following the recanalization, engineered PA constructs were perfused and flow was visualized using contrast agents and x-ray angiography. Further, computational fluid dynamics modeling was used to analyze flow in the recanalized model. Conclusions New 3D-printed and computational fluid dynamics models for vascular atresia were successfully created. We demonstrated the unique capability of a printed model to develop a novel technique for establishing blood flow in atretic vessels using clinical imaging, together with 3D bioprinting-based tissue engineering techniques. Additive biomanufacturing technologies can enable fabrication of functional vascular phantoms to model PA stenosis conditions that can help develop novel clinical applications.