Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale

The capacity to map traits over large cohorts of individuals—phenomics—lags far behind the explosive development in genomics. For microbes, the estimation of growth is the key phenotype because of its link to fitness. We introduce an automated microbial phenomics framework that delivers accurate, precise, and highly resolved growth phenotypes at an unprecedented scale. Advancements were achieved through the introduction of transmissive scanning hardware and software technology, frequent acquisition of exact colony population size measurements, extraction of population growth rates from growth curves, and removal of spatial bias by reference-surface normalization. Our prototype arrangement automatically records and analyzes close to 100,000 growth curves in parallel. We demonstrate the power of the approach by extending and nuancing the known salt-defense biology in baker’s yeast. The introduced framework represents a major advance in microbial phenomics by providing high-quality data for extensive cohorts of individuals and generating well-populated and standardized phenomics database

The Munich MIDY Pig Biobank - A unique resource for studying organ crosstalk in diabetes

OBJECTIVE: The prevalence of diabetes mellitus and associated complications is steadily increasing. As a resource for studying systemic consequences of chronic insulin insufficiency and hyperglycemia, we established a comprehensive biobank of long-term diabetic INSC94Y transgenic pigs, a model of mutant INS gene-induced diabetes of youth (MIDY), and of wild-type (WT) littermates. METHODS: Female MIDY pigs (n = 4) were maintained with suboptimal insulin treatment for 2 years, together with female WT littermates (n = 5). Plasma insulin, C-peptide and glucagon levels were regularly determined using specific immunoassays. In addition, clinical chemical, targeted metabolomics, and lipidomics analyses were performed. At age 2 years, all pigs were euthanized, necropsied, and a broad spectrum of tissues was taken by systematic uniform random sampling procedures. Total beta cell volume was determined by stereological methods. A pilot proteome analysis of pancreas, liver, and kidney cortex was performed by label free proteomics. RESULTS: MIDY pigs had elevated fasting plasma glucose and fructosamine concentrations, C-peptide levels that decreased with age and were undetectable at 2 years, and an 82% reduced total beta cell volume compared to WT. Plasma glucagon and beta hydroxybutyrate levels of MIDY pigs were chronically elevated, reflecting hallmarks of poorly controlled diabetes in humans. In total, ∼1900 samples of different body fluids (blood, serum, plasma, urine, cerebrospinal fluid, and synovial fluid) as well as ∼17,000 samples from ∼50 different tissues and organs were preserved to facilitate a plethora of morphological and molecular analyses. Principal component analyses of plasma targeted metabolomics and lipidomics data and of proteome profiles from pancreas, liver, and kidney cortex clearly separated MIDY and WT samples. CONCLUSIONS: The broad spectrum of well-defined biosamples in the Munich MIDY Pig Biobank that will be available to the scientific community provides a unique resource for systematic studies of organ crosstalk in diabetes in a multi-organ, multi-omics dimension