Single nuclei transcriptomics of the in situ human limbal stem cell niche.

The corneal epithelium acts as a barrier to pathogens entering the eye; corneal epithelial cells are continuously renewed by uni-potent, quiescent limbal stem cells (LSCs) located at the limbus, where the cornea transitions to conjunctiva. There has yet to be a consensus on LSC markers and their transcriptome profile is not fully understood, which may be due to using cadaveric tissue without an intact stem cell niche for transcriptomics. In this study, we addressed this problem by using single nuclei RNA sequencing (snRNAseq) on healthy human limbal tissue that was immediately snap-frozen after excision from patients undergoing cataract surgery. We identified the quiescent LSCs as a sub-population of corneal epithelial cells with a low level of total transcript counts. Moreover, TP63, KRT15, CXCL14, and ITGß4 were found to be highly expressed in LSCs and transiently amplifying cells (TACs), which constitute the corneal epithelial progenitor populations at the limbus. The surface markers SLC6A6 and ITGß4 could be used to enrich human corneal epithelial cell progenitors, which were also found to specifically express the putative limbal progenitor cell markers MMP10 and AC093496.1.

Hypothesis-free phenotype prediction within a genetics-first framework.

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed 'rare', even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population. Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But here we show that additional discoveries can be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible genetic causes for developmental disorders that have eluded other established methods and present molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

Experimental and Computational Approaches to Direct Cell Reprogramming: Recent Advancement and Future Challenges.

The process of direct cell reprogramming, also named transdifferentiation, permits for the conversion of one mature cell type directly into another, without returning to a dedifferentiated state. This makes direct reprogramming a promising approach for the development of several cellular and tissue engineering therapies. To achieve the change in the cell identity, direct reprogramming requires an arsenal of tools that combine experimental and computational techniques. In the recent years, several methods of transdifferentiation have been developed. In this review, we will introduce the concept of direct cell reprogramming and its background, and cover the recent developments in the experimental and computational prediction techniques with their applications. We also discuss the challenges of translating this technology to clinical setting, accompanied with potential solutions.

A conserved quality-control pathway that mediates degradation of unassembled ribosomal proteins.

Overproduced yeast ribosomal protein (RP) Rpl26 fails to assemble into ribosomes and is degraded in the nucleus/nucleolus by a ubiquitin-proteasome system quality control pathway comprising the E2 enzymes Ubc4/Ubc5 and the ubiquitin ligase Tom1. tom1 cells show reduced ubiquitination of multiple RPs, exceptional accumulation of detergent-insoluble proteins including multiple RPs, and hypersensitivity to imbalances in production of RPs and rRNA, indicative of a profound perturbation to proteostasis. Tom1 directly ubiquitinates unassembled RPs primarily via residues that are concealed in mature ribosomes. Together, these data point to an important role for Tom1 in normal physiology and prompt us to refer to this pathway as ERISQ, for excess ribosomal protein quality control. A similar pathway, mediated by the Tom1 homolog Huwe1, restricts accumulation of overexpressed hRpl26 in human cells. We propose that ERISQ is a key element of the quality control machinery that sustains protein homeostasis and cellular fitness in eukaryotes.

Ribosomal proteins produced in excess are degraded by the ubiquitin-proteasome system.

Ribosome assembly is an essential process that consumes prodigious quantities of cellular resources. Ribosomal proteins cannot be overproduced in Saccharomyces cerevisiae because the excess proteins are rapidly degraded. However, the responsible quality control (QC) mechanisms remain poorly characterized. Here we demonstrate that overexpression of multiple proteins of the small and large yeast ribosomal subunits is suppressed. Rpl26 overexpressed from a plasmid can be detected in the nucleolus and nucleoplasm, but it largely fails to assemble into ribosomes and is rapidly degraded. However, if the endogenous RPL26 loci are deleted, plasmid-encoded Rpl26 assembles into ribosomes and localizes to the cytosol. Chemical and genetic perturbation studies indicate that overexpressed ribosomal proteins are degraded by the ubiquitin-proteasome system and not by autophagy. Inhibition of the proteasome led to accumulation of multiple endogenous ribosomal proteins in insoluble aggregates, consistent with the operation of this QC mechanism in the absence of ribosomal protein overexpression. Our studies reveal that ribosomal proteins that fail to assemble into ribosomes are rapidly distinguished from their assembled counterparts and ubiquitinated and degraded within the nuclear compartment.

Proteome-wide remodeling of protein location and function by stress.

Protein location and function can change dynamically depending on many factors, including environmental stress, disease state, age, developmental stage, and cell type. Here, we describe an integrative computational framework, called the conditional function predictor (CoFP; http://nbm.ajou.ac.kr/cofp/), for predicting changes in subcellular location and function on a proteome-wide scale. The essence of the CoFP approach is to cross-reference general knowledge about a protein and its known network of physical interactions, which typically pool measurements from diverse environments, against gene expression profiles that have been measured under specific conditions of interest. Using CoFP, we predict condition-specific subcellular locations, biological processes, and molecular functions of the yeast proteome under 18 specified conditions. In addition to highly accurate retrieval of previously known gold standard protein locations and functions, CoFP predicts previously unidentified condition-dependent locations and functions for nearly all yeast proteins. Many of these predictions can be confirmed using high-resolution cellular imaging. We show that, under DNA-damaging conditions, Tsr1, Caf120, Dip5, Skg6, Lte1, and Nnf2 change subcellular location and RNA polymerase I subunit A43, Ino2, and Ids2 show changes in DNA binding. Beyond specific predictions, this work reveals a global landscape of changing protein location and function, highlighting a surprising number of proteins that translocate from the mitochondria to the nucleus or from endoplasmic reticulum to Golgi apparatus under stress.

Genome-wide bimolecular fluorescence complementation analysis of SUMO interactome in yeast.

The definition of protein-protein interactions (PPIs) in the natural cellular context is essential for properly understanding various biological processes. So far, however, most large-scale PPI analyses have not been performed in the natural cellular context. Here, we describe the construction of a Saccharomyces cerevisiae fusion library in which each endogenous gene is C-terminally tagged with the N-terminal fragment of Venus (VN) for a genome-wide bimolecular fluorescence complementation assay, a powerful technique for identifying PPIs in living cells. We illustrate the utility of the VN fusion library by systematically analyzing the interactome of the small ubiquitin-related modifier (SUMO) and provide previously unavailable information on the subcellular localization, types, and protease dependence of SUMO interactions. Our data set is highly complementary to the existing data sets and represents a useful resource for expanding the understanding of the physiological roles of SUMO. In addition, the VN fusion library provides a useful research tool that makes it feasible to systematically analyze PPIs in the natural cellular context.

Nsi1 plays a significant role in the silencing of ribosomal DNA in Saccharomyces cerevisiae.

In eukaryotic cells, ribosomal DNA (rDNA) forms the basis of the nucleolus. In Saccharomyces cerevisiae, 100-200 copies of a 9.1-kb rDNA repeat exist as a tandem array on chromosome XII. The stability of this highly repetitive array is maintained through silencing. However, the precise mechanisms that regulate rDNA silencing are poorly understood. Here, we report that S. cerevisiae Ydr026c, which we name NTS1 silencing protein 1 (Nsi1), plays a significant role in rDNA silencing. By studying the subcellular localization of 159 nucleolar proteins, we identified 11 proteins whose localization pattern is similar to that of Net1, a well-established rDNA silencing factor. Among these proteins is Nsi1, which is associated with the NTS1 region of rDNA and is required for rDNA silencing at NTS1. In addition, Nsi1 physically interacts with the known rDNA silencing factors Net1, Sir2 and Fob1. The loss of Nsi1 decreases the association of Sir2 with NTS1 and increases histone acetylation at NTS1. Furthermore, Nsi1 contributes to the longevity of yeast cells. Taken together, our findings suggest that Nsi1 is a new rDNA silencing factor that contributes to rDNA stability and lifespan extension in S. cerevisiae.

Rewiring of genetic networks in response to DNA damage.

Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They are very effective at identifying DNA repair pathways, highlighting new damage-dependent roles for the Slt2 kinase, Pph3 phosphatase, and histone variant Htz1. The data also reveal that protein complexes are generally stable in response to perturbation, but the functional relations between these complexes are substantially reorganized. Differential networks chart a new type of genetic landscape that is invaluable for mapping cellular responses to stimuli.

Biological characterization and structure based prediction of insulin-like growth factor binding protein-5.

The insulin-like growth factor binding protein (IGFBP) family has been shown to play a role in various functions such as cell growth, cell death, cell motility, and tissue remodeling. Among the 7 IGFBP family members, IGFBP-5 was recently shown to play an important role in breast cancer biology, especially in breast cancer metastasis. The three-dimensional structure of the mini IGFBP-5 domain (amino acids 40-92) is known, but structural information on the complete N, L, and C domains remains unknown. Due to difficulties associated with expression and crystallization of full-length IGFBP-5, fragments have more frequently been studied. In this study, IGFBP-5 structures containing N, L, and C domains were separately modeled from solved structures in protein data bank (PDB). In addition, the L domain of IGFBP-5 was expressed in Escherichia coli and purified for studying its structural characterization. Despite very low sequence homology, the novel L domain structure of IGFBP-5 was unexpectedly similar to that of the corepressor of repressor element-1 silencing transcription factor (CoREST) linker in the lysine-specific demethylase 1 (LSD1)-CoREST complex. The purified L domain existed as a homogenous dimer in glutaraldehyde cross-linking and exhibited a typical α-helix structure in the circular dichroism (CD) assay. This study has potential applications in medicine and other fields such as drug design, mutational study, and disease prediction.

In vivo quantification of protein-protein interactions in Saccharomyces cerevisiae using bimolecular fluorescence complementation assay.

Most of the biological processes are carried out and regulated by dynamic networks of protein-protein interactions. In this study, we demonstrate the feasibility of the bimolecular fluorescence complementation (BiFC) assay for in vivo quantitative analysis of protein-protein interactions in Saccharomyces cerevisiae. We show that the BiFC assay can be used to quantify not only the amount but also the cell-to-cell variation of protein-protein interactions in S. cerevisiae. In addition, we show that protein sumoylation and condition-specific protein-protein interactions can be quantitatively analyzed by using the BiFC assay. Taken together, our results validate that the BiFC assay is a very effective method for quantitative analysis of protein-protein interactions in living yeast cells and has a great potential as a versatile tool for the study of protein function.

Protein networks markedly improve prediction of subcellular localization in multiple eukaryotic species.

The function of a protein is intimately tied to its subcellular localization. Although localizations have been measured for many yeast proteins through systematic GFP fusions, similar studies in other branches of life are still forthcoming. In the interim, various machine-learning methods have been proposed to predict localization using physical characteristics of a protein, such as amino acid content, hydrophobicity, side-chain mass and domain composition. However, there has been comparatively little work on predicting localization using protein networks. Here, we predict protein localizations by integrating an extensive set of protein physical characteristics over a protein's extended protein-protein interaction neighborhood, using a classification framework called 'Divide and Conquer k-Nearest Neighbors' (DC-kNN). These predictions achieve significantly higher accuracy than two well-known methods for predicting protein localization in yeast. Using new GFP imaging experiments, we show that the network-based approach can extend and revise previous annotations made from high-throughput studies. Finally, we show that our approach remains highly predictive in higher eukaryotes such as fly and human, in which most localizations are unknown and the protein network coverage is less substantial.

Epigenetic deregulation of the human Oct4 promoter in mouse cells.

To examine whether the epigenetic status of the human Oct4 promoter is similarly regulated in mouse cells, we engineered a human bacterial artificial chromosome to express green fluorescent protein under the control of the hOct4 promoter and stably integrated it into mouse embryonic stem cells (mESCs), NIH3T3, and 293T cells. The hOct4 promoter is unmethylated in mESCs and it undergoes methylation during retinoic acid-induced differentiation. However, the hOct4 promoter is demethylated in NIH3T3 cells even though it is fully methylated in 293T cells. Methylation status of the hOct4 promoter is associated with green fluorescent protein expression at transcription level. Our findings indicate that the hOct4 promoter is differently regulated in mouse cells.

A vector system for efficient and economical switching of C-terminal epitope tags in Saccharomyces cerevisiae.

In Saccharomyces cerevisiae, one-step PCR-mediated modification of chromosomal genes allows fast and efficient tagging of yeast proteins with various epitopes at the C- or N-terminus. For many purposes, C-terminal tagging is advantageous in that the expression pattern of epitope tag is comparable to that of the authentic protein and the possibility for the tag to affect normal folding of polypeptide chain during translation is minimized. As experiments are getting complicated, it is often necessary to construct several fusion proteins tagged with various kinds of epitopes. Here, we describe development of a series of plasmids that allow efficient and economical switching of C-terminally tagged epitopes, using just one set of universal oligonucleotide primers. Containing a variety of epitopes (GFP, TAP, GST, Myc, HA and FLAG tag) and Kluyveromyces lactis URA3 gene as a selectable marker, the plasmids can be used to replace any MX6 module-based C-terminal epitope tag with one of the six epitopes. Furthermore, the plasmids also allow additional C-terminal epitope tagging of proteins in yeast cells that already carry MX6 module-based gene deletion or C-terminal epitope tag.

Bimolecular fluorescence complementation analysis system for in vivo detection of protein-protein interaction in Saccharomyces cerevisiae.

The bimolecular fluorescence complementation (BiFC) assay has been widely accepted for studying in vivo detection of protein-protein interactions in several organisms. To facilitate the application of the BiFC assay to yeast research, we have created a series of plasmids that allow single-step, PCR-based C- or N-terminal tagging of yeast proteins with yellow fluorescent protein fragments for BiFC assay. By examination of several interacting proteins (Sis1-Sis1, Net1-Sir2, Cet1-Cet1 and Pho2-Pho4), we demonstrate that the BiFC assay can be used to reliably analyse the occurrence and subcellular localization of protein-protein interactions in living yeast cells. The sequences for the described plasmids were submitted to the GenBank under Accession Nos: EF210802, pFA6a-VN-His3MX6; EF210803, pFA6a-VC-His3MX6; EF210804, pFA6a-VN-TRP1; EF210807, pFA6a-VC-TRP1; EF210808, pFA6a-VN-kanMX6; EF210809, pFA6a-VC-kanMX6; EF210810, pFA6a-His3MX6-P(GAL1)-VN; EF210805, pFA6a-His3MX6-P(GAL1)-VC; EF210806, pFA6a-TRP1-P(GAL1)-VN; EF210811, pFA6a-TRP1-P(GAL1)-VC; EF210812, pFA6a-kanMX6-P(GAL1)-VN; EF210813, pFA6a-kanMX6-P(GAL1)-VC; EF521883, pFA6a-His3MX6-P(CET1)-VN; EF521884, pFA6a-His3MX6-P(CET1)-VC; EF521885, pFA6a-TRP1-P(CET1)-VN; EF521886, pFA6a-TRP1-P(CET1)-VC; EF521887, pFA6a-kanMX6-P(CET1)-VN; EF521888, pFA6a-kanMX6-P(CET1)-VC.