DNA polymerase delta governs parental histone transfer to DNA replication lagging strand.

Chromatin replication is intricately intertwined with the recycling of parental histones to the newly duplicated DNA strands for faithful genetic and epigenetic inheritance. The transfer of parental histones occurs through two distinct pathways: leading strand deposition, mediated by the DNA polymerase ε subunits Dpb3/Dpb4, and lagging strand deposition, facilitated by the MCM helicase subunit Mcm2. However, the mechanism of the facilitation of Mcm2 transferring parental histones to the lagging strand while moving along the leading strand remains unclear. Here, we show that the deletion of Pol32, a nonessential subunit of major lagging-strand DNA polymerase δ, results in a predominant transfer of parental histone H3-H4 to the leading strand during replication. Biochemical analyses further demonstrate that Pol32 can bind histone H3-H4 both in vivo and in vitro. The interaction of Pol32 with parental histone H3-H4 is disrupted through the mutation of the histone H3-H4 binding domain within Mcm2. Our findings identify the DNA polymerase δ subunit Pol32 as a critical histone chaperone downstream of Mcm2, mediating the transfer of parental histones to the lagging strand during DNA replication.

Defective transfer of parental histone decreases frequency of homologous recombination by increasing free histone pools in budding yeast.

Recycling of parental histones is an important step in epigenetic inheritance. During DNA replication, DNA polymerase epsilon subunit DPB3/DPB4 and DNA replication helicase subunit MCM2 are involved in the transfer of parental histones to the leading and lagging strands, respectively. Single Dpb3 deletion (dpb3Δ) or Mcm2 mutation (mcm2-3A), which each disrupts one parental histone transfer pathway, leads to the other's predominance. However, the biological impact of the two histone transfer pathways on chromatin structure and DNA repair remains elusive. In this study, we used budding yeast Saccharomyces cerevisiae to determine the genetic and epigenetic outcomes from disruption of parental histone H3-H4 tetramer transfer. We found that a dpb3Δ mcm2-3A double mutant did not exhibit the asymmetric parental histone patterns caused by a single dpb3Δ or mcm2-3A mutation, suggesting that the processes by which parental histones are transferred to the leading and lagging strands are independent. Surprisingly, the frequency of homologous recombination was significantly lower in dpb3Δ, mcm2-3A and dpb3Δ mcm2-3A mutants, likely due to the elevated levels of free histones detected in the mutant cells. Together, these findings indicate that proper transfer of parental histones during DNA replication is essential for maintaining chromatin structure and that lower homologous recombination activity due to parental histone transfer defects is detrimental to cells.

Multi-omic integration by machine learning (MIMaL).

MOTIVATION: Cells respond to environments by regulating gene expression to exploit resources optimally. Recent advances in technologies allow for measuring the abundances of RNA, proteins, lipids and metabolites. These highly complex datasets reflect the states of the different layers in a biological system. Multi-omics is the integration of these disparate methods and data to gain a clearer picture of the biological state. Multi-omic studies of the proteome and metabolome are becoming more common as mass spectrometry technology continues to be democratized. However, knowledge extraction through the integration of these data remains challenging. RESULTS: Connections between molecules in different omic layers were discovered through a combination of machine learning and model interpretation. Discovered connections reflected protein control (ProC) over metabolites. Proteins discovered to control citrate were mapped onto known genetic and metabolic networks, revealing that these protein regulators are novel. Further, clustering the magnitudes of ProC over all metabolites enabled the prediction of five gene functions, each of which was validated experimentally. Two uncharacterized genes, YJR120W and YDL157C, were accurately predicted to modulate mitochondrial translation. Functions for three incompletely characterized genes were also predicted and validated, including SDH9, ISC1 and FMP52. A website enables results exploration and also MIMaL analysis of user-supplied multi-omic data. AVAILABILITY AND IMPLEMENTATION: The website for MIMaL is at https://mimal.app. Code for the website is at https://github.com/qdickinson/mimal-website. Code to implement MIMaL is at https://github.com/jessegmeyerlab/MIMaL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences.

Machine learning with multi-layered artificial neural networks, also known as "deep learning," is effective for making biological predictions. However, model interpretation is challenging, especially for sequential input data used with recurrent neural network architectures. Here, we introduce a framework called "Positional SHAP" (PoSHAP) to interpret models trained from biological sequences by utilizing SHapely Additive exPlanations (SHAP) to generate positional model interpretations. We demonstrate this using three long short-term memory (LSTM) regression models that predict peptide properties, including binding affinity to major histocompatibility complexes (MHC), and collisional cross section (CCS) measured by ion mobility spectrometry. Interpretation of these models with PoSHAP reproduced MHC class I (rhesus macaque Mamu-A1*001 and human A*11:01) peptide binding motifs, reflected known properties of peptide CCS, and provided new insights into interpositional dependencies of amino acid interactions. PoSHAP should have widespread utility for interpreting a variety of models trained from biological sequences.

Correction: Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.

[This corrects the article DOI: 10.1371/journal.pgen.1006372.].

Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.

The inability of native Saccharomyces cerevisiae to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram S. cerevisiae to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved S. cerevisiae strains depends upon epistatic interactions among genes encoding a xylose reductase (GRE3), a component of MAP Kinase (MAPK) signaling (HOG1), a regulator of Protein Kinase A (PKA) signaling (IRA2), and a scaffolding protein for mitochondrial iron-sulfur (Fe-S) cluster biogenesis (ISU1). Interestingly, the mutation in IRA2 only impacted anaerobic xylose consumption and required the loss of ISU1 function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in HOG1 and ISU1 unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.

Chemical genomic guided engineering of gamma-valerolactone tolerant yeast.

BACKGROUND: Gamma valerolactone (GVL) treatment of lignocellulosic bomass is a promising technology for degradation of biomass for biofuel production; however, GVL is toxic to fermentative microbes. Using a combination of chemical genomics with the yeast (Saccharomyces cerevisiae) deletion collection to identify sensitive and resistant mutants, and chemical proteomics to monitor protein abundance in the presence of GVL, we sought to understand the mechanism toxicity and resistance to GVL with the goal of engineering a GVL-tolerant, xylose-fermenting yeast. RESULTS: Chemical genomic profiling of GVL predicted that this chemical affects membranes and membrane-bound processes. We show that GVL causes rapid, dose-dependent cell permeability, and is synergistic with ethanol. Chemical genomic profiling of GVL revealed that deletion of the functionally related enzymes Pad1p and Fdc1p, which act together to decarboxylate cinnamic acid and its derivatives to vinyl forms, increases yeast tolerance to GVL. Further, overexpression of Pad1p sensitizes cells to GVL toxicity. To improve GVL tolerance, we deleted PAD1 and FDC1 in a xylose-fermenting yeast strain. The modified strain exhibited increased anaerobic growth, sugar utilization, and ethanol production in synthetic hydrolysate with 1.5% GVL, and under other conditions. Chemical proteomic profiling of the engineered strain revealed that enzymes involved in ergosterol biosynthesis were more abundant in the presence of GVL compared to the background strain. The engineered GVL strain contained greater amounts of ergosterol than the background strain. CONCLUSIONS: We found that GVL exerts toxicity to yeast by compromising cellular membranes, and that this toxicity is synergistic with ethanol. Deletion of PAD1 and FDC1 conferred GVL resistance to a xylose-fermenting yeast strain by increasing ergosterol accumulation in aerobically grown cells. The GVL-tolerant strain fermented sugars in the presence of GVL levels that were inhibitory to the unmodified strain. This strain represents a xylose fermenting yeast specifically tailored to GVL produced hydrolysates.

Mechanism of imidazolium ionic liquids toxicity in Saccharomyces cerevisiae and rational engineering of a tolerant, xylose-fermenting strain.

BACKGROUND: Imidazolium ionic liquids (IILs) underpin promising technologies that generate fermentable sugars from lignocellulose for future biorefineries. However, residual IILs are toxic to fermentative microbes such as Saccharomyces cerevisiae, making IIL-tolerance a key property for strain engineering. To enable rational engineering, we used chemical genomic profiling to understand the effects of IILs on S. cerevisiae. RESULTS: We found that IILs likely target mitochondria as their chemical genomic profiles closely resembled that of the mitochondrial membrane disrupting agent valinomycin. Further, several deletions of genes encoding mitochondrial proteins exhibited increased sensitivity to IIL. High-throughput chemical proteomics confirmed effects of IILs on mitochondrial protein levels. IILs induced abnormal mitochondrial morphology, as well as altered polarization of mitochondrial membrane potential similar to valinomycin. Deletion of the putative serine/threonine kinase PTK2 thought to activate the plasma-membrane proton efflux pump Pma1p conferred a significant IIL-fitness advantage. Conversely, overexpression of PMA1 conferred sensitivity to IILs, suggesting that hydrogen ion efflux may be coupled to influx of the toxic imidazolium cation. PTK2 deletion conferred resistance to multiple IILs, including [EMIM]Cl, [BMIM]Cl, and [EMIM]Ac. An engineered, xylose-converting ptk2∆ S. cerevisiae (Y133-IIL) strain consumed glucose and xylose faster and produced more ethanol in the presence of 1 % [BMIM]Cl than the wild-type PTK2 strain. We propose a model of IIL toxicity and resistance. CONCLUSIONS: This work demonstrates the utility of chemical genomics-guided biodesign for development of superior microbial biocatalysts for the ever-changing landscape of fermentation inhibitors.

The Role of Hexokinases in Epigenetic Regulation: Altered Hexokinase Expression and Chromatin Stability in Yeast.

Background . Human hexokinase 2 ( HK2 ) plays an important role in regulating Warburg effect, which metabolizes glucose to lactate acid even in the presence of ample oxygen and provides intermediate metabolites to support cancer cell proliferation and tumor growth. HK2 overexpression has been observed in various types of cancers and targeting HK2 -driven Warburg effect has been suggested as a potential cancer therapeutic strategy. Given that epigenetic enzymes utilize metabolic intermediates as substrates or co-factors to carry out post-translational modification of DNA and histones in cells, we hypothesized that altering HK2 expression-mediated cellular glycolysis rates could impact the epigenome and, consequently, genome stability in yeast. To test this hypothesis, we established genetic models with different yeast hexokinase 2 ( HXK2) expression in Saccharomyces cerevisiae yeast cells and investigated the effect of HXK2 -dependent metabolism on parental nucleosome transfer, a key DNA replication-coupled epigenetic inheritance process, and chromatin stability. Results . By comparing the growth of mutant yeast cells carrying single deletion of hxk1Δ , hxk2Δ , or double-loss of hxk1Δ hxk2Δ to wild-type cells, we demonstrated that HXK2 is the dominant HXK in yeast cell growth. Surprisingly, manipulating HXK2 expression in yeast, whether through overexpression or deletion, had only a marginal impact on parental nucleosome assembly, but a noticeable trend with decrease chromatin instability. However, targeting yeast cells with 2-deoxy-D-glucose (2-DG), a HK2 inhibitor that has been proposed as an anti-cancer treatment, significantly increased chromatin instability. Conclusion . Our findings suggest that in yeast cells lacking HXK2 , alternative HXK s such as HXK1 or glucokinase 1 ( GLK1 ) play a role in supporting glycolysis at a level that adequately maintain epigenomic stability. While our study demonstrated an increase in epigenetic instability with 2-DG treatment, the observed effect seemed to occur independently of Hxk2-mediated glycolysis inhibition. Thus, additional research is needed to identify the molecular mechanism through which 2-DG influences chromatin stability.

Phase variable acetylation of lipooligosaccharide modifies antibody production and opsonophagocytic killing of non-typeable Haemophilus influenzae.

Non-typeable Haemophilus influenzae (NTHi) causes millions of infections each year. Though it is primarily known to cause otitis media, recent studies have shown NTHi is emerging as a primary pathogen for invasive infection, prompting the need for new vaccines and treatments. Lipooligosaccharide (LOS) has been identified as a potential vaccine candidate due to its immunogenic nature and outer membrane localization. Yet, phase variable expression of genes involved in LOS synthesis has complicated vaccine development. In this study, we used a chinchilla model of otitis media to investigate how phase variation of oafA, a gene involved in LOS biosynthesis, affects antibody production in response to infection. We found that acetylation of LOS by OafA inhibited production of LOS-specific antibodies during infection and that NTHi expressing acetylated LOS were subsequently better protected against opsonophagocytic killing. These findings highlight the importance of understanding how phase variable modifications might affect vaccine efficacy and success.

Natural Variation in the Multidrug Efflux Pump SGE1 Underlies Ionic Liquid Tolerance in Yeast.

Imidazolium ionic liquids (IILs) have a range of biotechnological applications, including as pretreatment solvents that extract cellulose from plant biomass for microbial fermentation into sustainable bioenergy. However, residual levels of IILs, such as 1-ethyl-3-methylimidazolium chloride ([C2C1im]Cl), are toxic to biofuel-producing microbes, including the yeast Saccharomyces cerevisiae. S. cerevisiae strains isolated from diverse ecological niches differ in genomic sequence and in phenotypes potentially beneficial for industrial applications, including tolerance to inhibitory compounds present in hydrolyzed plant feedstocks. We evaluated >100 genome-sequenced S. cerevisiae strains for tolerance to [C2C1im]Cl and identified one strain with exceptional tolerance. By screening a library of genomic DNA fragments from the [C2C1im]Cl-tolerant strain for improved IIL tolerance, we identified SGE1, which encodes a plasma membrane multidrug efflux pump, and a previously uncharacterized gene that we named ionic liquid tolerance 1 (ILT1), which encodes a predicted membrane protein. Analyses of SGE1 sequences from our panel of S. cerevisiae strains together with growth phenotypes implicated two single nucleotide polymorphisms (SNPs) that associated with IIL tolerance and sensitivity. We confirmed these phenotypic effects by transferring the SGE1 SNPs into a [C2C1im]Cl-sensitive yeast strain using CRISPR/Cas9 genome editing. Further studies indicated that these SNPs affect Sge1 protein stability and cell surface localization, influencing the amount of toxic IILs that cells can pump out of the cytoplasm. Our results highlight the general potential for discovering useful biotechnological functions from untapped natural sequence variation and provide functional insight into emergent SGE1 alleles with reduced capacities to protect against IIL toxicity.

Inhibition of microbial biofuel production in drought-stressed switchgrass hydrolysate.

BACKGROUND: Interannual variability in precipitation, particularly drought, can affect lignocellulosic crop biomass yields and composition, and is expected to increase biofuel yield variability. However, the effect of precipitation on downstream fermentation processes has never been directly characterized. In order to investigate the impact of interannual climate variability on biofuel production, corn stover and switchgrass were collected during 3 years with significantly different precipitation profiles, representing a major drought year (2012) and 2 years with average precipitation for the entire season (2010 and 2013). All feedstocks were AFEX (ammonia fiber expansion)-pretreated, enzymatically hydrolyzed, and the hydrolysates separately fermented using xylose-utilizing strains of Saccharomyces cerevisiae and Zymomonas mobilis. A chemical genomics approach was also used to evaluate the growth of yeast mutants in the hydrolysates. RESULTS: While most corn stover and switchgrass hydrolysates were readily fermented, growth of S. cerevisiae was completely inhibited in hydrolysate generated from drought-stressed switchgrass. Based on chemical genomics analysis, yeast strains deficient in genes related to protein trafficking within the cell were significantly more resistant to the drought-year switchgrass hydrolysate. Detailed biomass and hydrolysate characterization revealed that switchgrass accumulated greater concentrations of soluble sugars in response to the drought and these sugars were subsequently degraded to pyrazines and imidazoles during ammonia-based pretreatment. When added ex situ to normal switchgrass hydrolysate, imidazoles and pyrazines caused anaerobic growth inhibition of S. cerevisiae. CONCLUSIONS: In response to the osmotic pressures experienced during drought stress, plants accumulate soluble sugars that are susceptible to degradation during chemical pretreatments. For ammonia-based pretreatment, these sugars degrade to imidazoles and pyrazines. These compounds contribute to S. cerevisiae growth inhibition in drought-year switchgrass hydrolysate. This work discovered that variation in environmental conditions during the growth of bioenergy crops could have significant detrimental effects on fermentation organisms during biofuel production. These findings are relevant to regions where climate change is predicted to cause an increased incidence of drought and to marginal lands with poor water-holding capacity, where fluctuations in soil moisture may trigger frequent drought stress response in lignocellulosic feedstocks.