Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p<10-16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC (sites VCF available via FTP at ftp.broadinstitute.org/pub/ExAC_release/release0.3/) to pinpoint genetic variation that contributes to variable disease predisposition across populations

Correction: Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population

Correction of 2018 article: PLoS Genet 14(5): e1007329. https://doi.org/10.1371/journal.pgen.1007329 PMID: 2979557

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Enhancing antibody folding and secretion by tailoring the Saccharomyces cerevisiae endoplasmic reticulum

Background: The yeast Saccharomyces cerevisiae provides intriguing possibilities for synthetic biology and bioprocess applications, but its use is still constrained by cellular characteristics that limit the product yields. Considering the production of advanced biopharmaceuticals, a major hindrance lies in the yeast endoplasmic reticulum (ER), as it is not equipped for efficient and large scale folding of complex proteins, such as human antibodies. Results: Following the example of professional secretory cells, we show that inducing an ER expansion in yeast by deleting the lipid-regulator gene OPI1 can improve the secretion capacity of full-length antibodies up to fourfold. Based on wild-type and ER-enlarged yeast strains, we conducted a screening of a folding factor overexpression library to identify proteins and their expression levels that enhance the secretion of antibodies. Out of six genes tested, addition of the peptidyl-prolyl isomerase CPR5 provided the most beneficial effect on specific product yield while PDI1, ERO1, KAR2, LHS1 and SIL1 had a mild or even negative effect to antibody secretion efficiency. Combining genes for ER enhancement did not induce any significant additional effect compared to addition of just one element. By combining the Δopi1 strain, with the enlarged ER, with CPR5 overexpression, we were able to boost the specific antibody product yield by a factor of 10 relative to the non-engineered strain. Conclusions: Engineering protein folding in vivo is a major task for biopharmaceuticals production in yeast and needs to be optimized at several levels. By rational strain design and high-throughput screening applications we were able to increase the specific secreted antibody yields of S. cerevisiae up to 10-fold, providing a promising strain for further process optimization and platform development for antibody production.Peer reviewe

Glycoengineering of yeasts from the perspective of glycosylation efficiency

Peer reviewe

High-throughput protein production in yeast

32 p.-2 fig. High-Throughput Protein Production in Yeast. In: Vincentelli R. (eds) High-Throughput Protein Production and Purification. Methods in Molecular Biology, vol 2025. Humana, New York, NY (2019)Yeasts are versatile single-celled fungi that grow to high cell densities on inexpensive media. With well-studied genetics and metabolism and a wealth of knowledge available about their propagation and growth in academic as well as industrial settings, yeasts have long been used for recombinant protein production of isolated proteins and multisubunit complexes. They can be easily adapted to high-throughput protein expression pipelines. Importantly, the outcome from small-scale expression evaluations in high-throughput mode is scalable to laboratory and industrial scales using well-established procedures. In this chapter, we offer a state-of-the-art perspective on currently available high-throughput pipelines for protein production in S. cerevisiae and P. pastoris and discuss future challenges and avenues for improvement.MCV has received funding from the SpanishMinisterio de Economía y Competitividad (CTQ2015-66206-C2-2-R and SAF2015-72961-EXP) and the Regional Government of Madrid (S2017/BMD-3673).Peer reviewe