In vitro mucus transportability, cytogenotoxicity, and hematological changes as non-destructive physiological biomarkers in fish chronically exposed to metals.

The biomonitoring of fish using biomarkers represents a useful tool for the assessment of aquatic pollution. This study evaluated the sublethal toxic effects of aquatic pollution on fish collected from a site contaminated by metals. Water and fish (Oreochromis niloticus) samples were collected from a pond in the Parque Ecológico do Tietê (PET) that lies along the Tietê River (São Paulo, Brazil), and from a control site (an experimental fish farm). The metal content of the water was evaluated, and fish were used to examine the properties of gill mucus and blood. The PET fish were evaluated for alterations in the in vitro transportability of mucus and changes in blood properties (e.g., cell volume, hemoglobin concentration, red blood cells, and white blood cell count). The results of the water analyzes indicated metal levels above the legal standards for Fe (0.71 mg/L), Ni (0.06 mg/L), Mn (0.11 mg/L), and Pb (0.48 mg/L). Compared to the controls, the hematologic parameter analyzes of PET fish revealed significantly higher numbers of erythrocytes (RBC), leukocytes (WBC), lymphocytes, erythroblasts, and Mean Corpuscular Volume (MCV); however, the hemoglobin content and Mean Corpuscular Hemoglobin Concentration (MCHC) values were significantly lower. The frequencies of nuclear abnormalities and micronuclei were significantly higher and the mucociliary transport was significantly lower in PET fish than in the controls. These results suggest that fish from the contaminated site exhibit a series of physiological responses, which probably indicate health disturbances. Furthermore, the results suggest that blood and mucus are promising, non-destructive targets for use in the monitoring of pollution.

An open-source FACS automation system for high-throughput cell biology.

Recent advances in gene editing are enabling the engineering of cells with an unprecedented level of scale. To capitalize on this opportunity, new methods are needed to accelerate the different steps required to manufacture and handle engineered cells. Here, we describe the development of an integrated software and hardware platform to automate Fluorescence-Activated Cell Sorting (FACS), a central step for the selection of cells displaying desired molecular attributes. Sorting large numbers of samples is laborious, and, to date, no automated system exists to sequentially manage FACS samples, likely owing to the need to tailor sorting conditions ("gating") to each individual sample. Our platform is built around a commercial instrument and integrates the handling and transfer of samples to and from the instrument, autonomous control of the instrument's software, and the algorithmic generation of sorting gates, resulting in walkaway functionality. Automation eliminates operator errors, standardizes gating conditions by eliminating operator-to-operator variations, and reduces hands-on labor by 93%. Moreover, our strategy for automating the operation of a commercial instrument control software in the absence of an Application Program Interface (API) exemplifies a universal solution for other instruments that lack an API. Our software and hardware designs are fully open-source and include step-by-step build documentation to contribute to a growing open ecosystem of tools for high-throughput cell biology.

OpenCell: Endogenous tagging for the cartography of human cellular organization.

Elucidating the wiring diagram of the human cell is a central goal of the postgenomic era. We combined genome engineering, confocal live-cell imaging, mass spectrometry, and data science to systematically map the localization and interactions of human proteins. Our approach provides a data-driven description of the molecular and spatial networks that organize the proteome. Unsupervised clustering of these networks delineates functional communities that facilitate biological discovery. We found that remarkably precise functional information can be derived from protein localization patterns, which often contain enough information to identify molecular interactions, and that RNA binding proteins form a specific subgroup defined by unique interaction and localization properties. Paired with a fully interactive website (opencell.czbiohub.org), our work constitutes a resource for the quantitative cartography of human cellular organization.