High-throughput classification of S. cerevisiae tetrads using deep learning.

Meiotic crossovers play a vital role in proper chromosome segregation and evolution of most sexually reproducing organisms. Meiotic recombination can be visually observed in Saccharomyces cerevisiae tetrads using linked spore-autonomous fluorescent markers placed at defined intervals within the genome, which allows for analysis of meiotic segregation without the need for tetrad dissection. To automate the analysis, we developed a deep learning-based image recognition and classification pipeline for high-throughput tetrad detection and meiotic crossover classification. As a proof of concept, we analyzed a large image data set from wild-type and selected gene knock-out mutants to quantify crossover frequency, interference, chromosome missegregation, and gene conversion events. The deep learning-based method has the potential to accelerate the discovery of new genes involved in meiotic recombination in S. cerevisiae such as the underlying factors controlling crossover frequency and interference.

Destabilization and Degradation of a Disease-Linked PGM1 Protein Variant.

PGM1-linked congenital disorder of glycosylation (PGM1-CDG) is an autosomal recessive disease characterized by several phenotypes, some of which are life-threatening. Research focusing on the disease-related variants of the α-D-phosphoglucomutase 1 (PGM1) protein has shown that several are insoluble in vitro and expressed at low levels in patient fibroblasts. Due to these observations, we hypothesized that some disease-linked PGM1 protein variants are structurally destabilized and subject to protein quality control (PQC) and rapid intracellular degradation. Employing yeast-based assays, we show that a disease-associated human variant, PGM1 L516P, is insoluble, inactive, and highly susceptible to ubiquitylation and rapid degradation by the proteasome. In addition, we show that PGM1 L516P forms aggregates in S. cerevisiae and that both the aggregation pattern and the abundance of PGM1 L516P are chaperone-dependent. Finally, using computational methods, we perform saturation mutagenesis to assess the impact of all possible single residue substitutions in the PGM1 protein. These analyses identify numerous missense variants with predicted detrimental effects on protein function and stability. We suggest that many disease-linked PGM1 variants are subject to PQC-linked degradation and that our in silico site-saturated data set may assist in the mechanistic interpretation of PGM1 variants.

PICH deficiency limits the progression of MYC-induced B-cell lymphoma.

Plk1-interacting checkpoint helicase (PICH) is a DNA translocase involved in resolving ultrafine anaphase DNA bridges and, therefore, is important to safeguard chromosome segregation and stability. PICH is overexpressed in various human cancers, particularly in lymphomas such as Burkitt lymphoma, which is caused by MYC translocations. To investigate the relevance of PICH in cancer development and progression, we have combined novel PICH-deficient mouse models with the Eµ-Myc transgenic mouse model, which recapitulates B-cell lymphoma development. We have observed that PICH deficiency delays the onset of MYC-induced lymphomas in Pich heterozygous females. Moreover, using a Pich conditional knockout mouse model, we have found that Pich deletion in adult mice improves the survival of Eµ-Myc transgenic mice. Notably, we show that Pich deletion in healthy adult mice is well tolerated, supporting PICH as a suitable target for anticancer therapies. Finally, we have corroborated these findings in two human Burkitt lymphoma cell lines and we have found that the death of cancer cells was accompanied by chromosomal instability. Based on these findings, we propose PICH as a potential therapeutic target for Burkitt lymphoma and for other cancers where PICH is overexpressed.