Corrigendum: Phylogenetic and genomic analyses of two new species of Clavispora (Metschnikowiaceae, Saccharomycetales) from Central China

[This corrects the article DOI: 10.3389/fmicb.2022.1019599.].

Parachryseolinea silvisoli gen. nov., sp. nov., isolated from forest soil, and reclassification of Chryseolinea flava as Pseudochryseolinea flava gen. nov., comb. nov

A lemon-chiffon strain, designated QH1ED-6-2^T, was isolated from a soil sample collected from Qinghai Virgin Forests, Qinghai Province, PR China. The strain was Gram-stain-negative, aerobic, rod-shaped and motile by gliding. Phylogenetic analysis of 16S rRNA gene sequences revealed that strain QH1ED-6-2^T belongs to the family Fulvivirgaceae, and has the highest similarity values of 93.6-92.0 % to Ohtaekwangia koreensis CCUG 58939^T, Ohtaekwangia kribbensis CCUG 58938^T, Chryseolinea flava SDU1-6^T and Chryseolinea serpens DSM 24574^T, respectively. The major cellular fatty acids included iso-C_15 : 0, C_16 : 1  ω5c, iso-C_17 : 0 3-OH and summed feature 3. The major polar lipid was phosphatidylethanolamine. The predominant respiratory quinone was menaquinone-7. The average amino acid identity values and percentages of conserved proteins between QH1ED-6-2^T and its closely related genera were 66.4-69.6 % and 58.9-64.9 %, respectively, which are interspersed in the intra-genera cutoff values. The digital DNA-DNA hybridization values were 17.6-19.2 %. The draft genome size of strain QH1ED-6-2^T was 7.98 Mbp with a DNA G+C content of 51.4 mol%. Based on phenotypic, chemotaxonomic, phylogenetic data, genomic DNA G+C content, as well as AAI, POCP and dDDH results, strain QH1ED-6-2^T represents a novel species of a new genus in the family Fulvivirgaceae, for which the name Parachryseolinea silvisoli sp. nov. is proposed. The type strain is QH1ED-6-2^T (=GDMCC 1.2318^T=JCM 35041^T). We also propose the reclassification of Chryseolinea flava as Pseudochryseolinea flava gen. nov., comb. nov. (type strain SDU1-6^T=CGMCC 1.13492^T=JCM 32520^T).

Enriched Random Forest for High Dimensional Genomic Data

Ensemble methods such as random forest works well on high-dimensional datasets. However, when the number of features is extremely large compared to the number of samples and the percentage of truly informative feature is very small, performance of traditional random forest decline significantly. To this end, we develop a novel approach that enhance the performance of traditional random forest by reducing the contribution of trees whose nodes are populated with less informative features. The proposed method selects eligible subsets at each node by weighted random sampling as opposed to simple random sampling in traditional random forest. We refer to this modified random forest algorithm as "Enriched Random Forest". Using several high-dimensional micro-array datasets, we evaluate the performance of our approach in both regression and classification settings. In addition, we also demonstrate the effectiveness of balanced leave-one-out cross-validation to reduce computational load and decrease sample size while computing feature weights. Overall, the results indicate that enriched random forest improves the prediction accuracy of traditional random forest, especially when relevant features are very few.

Genomic analyses of claw disorders in Holstein cows: Genetic parameters, trait associations, and genome-wide associations considering interactions of SNP and heat stress

The aim of the present study was an in-depth genomic analysis to understand the genomic mechanisms of the 3 claw disorders dermatitis digitalis (DD), interdigital hyperplasia (HYP), and sole ulcer (SU). In this regard, we estimated genetic parameters based on genomic relationship matrices, performed genome-wide association studies, annotated potential candidate genes, and inferred genetic associations with breeding goal traits considering the most important chromosomal segments. As a further novelty of this study, we inferred possible SNP × heat stress interactions for claw disorders. The study consisted of 17,264 first-lactation Holstein Friesian cows kept in 50 large-scale contract herds. The disease prevalence was 15.96, 2.36, and 8.20% for DD, HYP, and SU, respectively. The remaining breeding goal traits consisted of type traits of the feet and leg composite, female fertility, health traits, and 305-d production traits. The final genotype data set included 44,474 SNPs from the 17,264 genotyped cows. Heritabilities for DD, HYP, and SU were estimated in linear and threshold models considering the genomic relationship matrix (G matrix). Genetic correlations with breeding goal traits based on G were estimated in a series of bivariate linear models, which were verified via SNP effect correlations for specific chromosome segments (i.e., segments harboring potential candidate genes for DD, HYP, and SU). Genome-wide association studies were performed for all traits in a case-control design by applying a single SNP linear mixed model. Furthermore, for DD, HYP, and SU, we modeled SNP × heat stress interactions in genome-wide association studies. Single nucleotide polymorphism-based heritabilities were 0.04 and 0.08 for DD, 0.03 and 0.10 for SU, and 0.03 and 0.23 for HYP from linear and threshold models, respectively. The genetic correlations between DD, HYP, and SU with conformation traits from the feet and leg composite were positive throughout, indicating the value of indirect selection on conformation traits to improve claw health. Genetic correlations between DD, SU, and HYP with other breeding goal traits indicated impaired female fertility, impaired udder health status, and productivity decline of diseased cows. Genetic correlations among DD, SU, and HYP were moderate to large, indicating that different claw disorders have similar genetic mechanisms. Nevertheless, we identified disease-specific potential candidate genes, and genetic associations based on the surrounding SNPs partly differed from the genetic correlations. Especially for candidate genes contributing to 2 traits simultaneously, correlations based on SNP effects from the respective chromosome segment were close to 1 or to -1. In this regard, we annotated the candidate genes KRT33A and KRT33B for HYP and DD, KIF27 for HYP and calving to first insemination, and MAN1A1 for SU and the production traits. For SNP × heat stress interactions, we identified significant SNPs on BTA 2, 4, 5, 7, 8, 9, 13, 22, 25, and 28, and we annotated the potential candidate genes FSIP2, CLCN1, ADGRV1, DOP1A, THBD, and RHOBTB1. Results indicate gene-specific mechanisms of the claw disorders only in specific environments.

Dissemination Routes of Carbapenem and Pan-Aminoglycoside Resistance Mechanisms in Hospital and Urban Wastewater Canalizations of Ghana

Wastewater has a major role in antimicrobial resistance (AMR) dynamics and public health. The impact on AMR of wastewater flux at the community-hospital interface in low- and middle-income countries (LMICs) is poorly understood. Therefore, the present study analyzed the epidemiological scenario of resistance genes, mobile genetic elements (MGEs), and bacterial populations in wastewater around the Tamale metropolitan area (Ghana). Wastewater samples were collected from the drainage and canalizations before and after three hospitals and one urban waste treatment plant (UWTP). From all carbapenem/pan-aminoglycoside-resistant bacteria, 36 isolates were selected to determine bacterial species and phenotypical resistance profiles. Nanopore sequencing was used to screen resistance genes and plasmids, whereas, sequence types, resistome and plasmidome contents, pan-genome structures, and resistance gene variants were analyzed with Illumina sequencing. The combination of these sequencing data allowed for the resolution of the resistance gene-carrying platforms. Hospitals and the UWTP collected genetic and bacterial elements from community wastewater and amplified successful resistance gene-bacterium associations, which reached the community canalizations. Uncommon carbapenemase/β-lactamase gene variants, like bla_DIM-1, and novel variants, including bla_VIM-71, bla_CARB-53, and bla_CMY-172, were identified and seem to spread via clonal expansion of environmental Pseudomonas spp. However, bla_NDM-1, bla_CTX-M-15, and armA genes, among others, were associated with MGEs that allowed for their dissemination between environmental and clinical bacterial hosts. In conclusion, untreated hospital wastewater in Ghana is a hot spot for the emergence and spread of genes and gene-plasmid-bacterium associations that accelerate AMR, including to last-resort antibiotics. Urgent actions must be taken in wastewater management in LMICs in order to delay AMR expansion.

IMPORTANCE Antimicrobial resistance (AMR) is one the major threats to public health today, especially resistance to last-resort compounds for the treatment of critical infections, such as carbapenems and aminoglycosides. Innumerable works have focused on the clinical ambit of AMR, but studies addressing the impact of wastewater cycles on the emergence and dissemination of resistant bacteria are still limited. The lack of knowledge is even greater when referring to low- and middle-income countries, where there is an absence of accurate sanitary systems. Furthermore, the combination of short- and long-read sequencing has surpassed former technical limitations, allowing the complete characterization of resistance genes, mobile genetic platforms, plasmids, and bacteria. The present study deciphered the multiple elements and routes involved in AMR dynamics in wastewater canalizations and, therefore, in the local population of Tamale, providing the basis to adopt accurate control measures to preserve and promote public health.

Effect of Gamma Irradiation on Enhanced Biological Activities of Exopolysaccharide from Halomonas desertis G11: Biochemical and Genomic Insights

In this work, a native exopolysaccharide (nEPS) produced by Halomonas desertis G11 isolated from a Tunisian extreme environment was modified by gamma irradiation. Characterization as well as the antioxidant and antitumor activities of nEPS and its gamma-irradiated derivatives (iEPSs) were comparatively evaluated. In vitro and in vivo antioxidant potentials were determined by using different methods and through different antioxidant enzymes. The antitumor activity was checked against a human colon cancer cell line. Analyses of the complete genome sequence were carried out to identify genes implicated in the production of nEPS. Thus, the genomic biosynthesis pathway and the export mechanism of nEPS were proposed. Analyses of irradiation data showed that iEPSs acquired new functional groups, lower molecular weights, and gained significantly (p < 0.05) higher antioxidant and antitumor abilities compared with nEPS. These findings provide a basis for using iEPSs as novel pharmaceutical agents for human therapies.

Genomic Analyses of Penicillium Species Have Revealed Patulin and Citrinin Gene Clusters and Novel Loci Involved in Oxylipin Production

Blue mold of apple is caused by several different Penicillium species, among which P. expansum and P. solitum are the most frequently isolated. P. expansum is the most aggressive species, and P. solitum is very weak when infecting apple fruit during storage. In this study, we report complete genomic analyses of three different Penicillium species: P. expansum R21 and P. crustosum NJ1, isolated from stored apple fruit; and P. maximae 113, isolated in 2013 from a flooded home in New Jersey, USA, in the aftermath of Hurricane Sandy. Patulin and citrinin gene cluster analyses explained the lack of patulin production in NJ1 compared to R21 and lack of citrinin production in all three strains. A Drosophila bioassay demonstrated that volatiles emitted by P. solitum SA and P. polonicum RS1 were more toxic than those from P. expansum and P. crustosum strains (R27, R11, R21, G10, and R19). The toxicity was hypothesized to be related to production of eight-carbon oxylipins. Putative lipoxygenase genes were identified in P. expansum and P. maximae strains, but not in P. crustosum. Our data will provide a better understanding of Penicillium spp. complex secondary metabolic capabilities, especially concerning the genetic bases of mycotoxins and toxic VOCs.

The Virulence of S. marcescens Strains Isolated From Contaminated Blood Products Is Divergent in the C. elegans Infection Model

Bacterial contamination of platelet concentrates (PCs) can occur during blood donation or PC processing, necessitating routine screening to identify contaminated products in efforts to prevent adverse transfusion reactions in recipient patients. Serratia marcescens is a common bacterial contaminant, and its resilient nature coupled with genetic promiscuity imbue this environmental bacterium with resistance to disinfectants and antibiotics enhancing bacterial virulence. In this study, we aim to understand adaptive survival mechanisms through genetic characterization of two S. marcescens strains, CBS11 and CBS12, isolated from PCs by Canadian Blood Services. Genomic analyses of the two strains indicated that CBS11 has one chromosome and one plasmid (pAM01), whereas CBS12 has no plasmids. Phylogenetic analyses show that CBS11 and CBS12 are non-clonal strains, with CBS11 clustering closely with clinical strain CAV1492 and less so with environmental strain PWN146, and CBS12 clustering with a clinical strain AR_0027. Interestingly, pAM01 was most closely related to PWN146p1, a plasmid found in S. marcescens PWN146 strain associated with pinewood nematode Bursaphelenchus xylophilus. Lastly, the genomic diversity of CBS11 and CBS12 was not reflected in the antibiotic resistance profiles as they were remarkably similar to one another, but was reflected in the virulence phenotypes assessed in the Caenorhabditis elegans nematode infection model, with CBS11 being more virulent then CBS12. Taken together, we suggest that S. marcescens environmental isolates that feature evolutionary diverse genomics are better equipped to adapt and thrive in varied environments, such as that of PCs, and therefore is as much of a concern as multi-drug resistance for human infection potential.

Tracing Lung Cancer Risk Factors Through Mutational Signatures in Never-Smokers

Epidemiologic studies often rely on questionnaire data, exposure measurement tools, and/or biomarkers to identify risk factors and the underlying carcinogenic processes. An emerging and promising complementary approach to investigate cancer etiology is the study of somatic "mutational signatures" that endogenous and exogenous processes imprint on the cellular genome. These signatures can be identified from a complex web of somatic mutations thanks to advances in DNA sequencing technology and analytical algorithms. This approach is at the core of the Sherlock-Lung study (2018-ongoing), a retrospective case-only study of over 2,000 lung cancers in never-smokers (LCINS), using different patterns of mutations observed within LCINS tumors to trace back possible exposures or endogenous processes. Whole genome and transcriptome sequencing, genome-wide methylation, microbiome, and other analyses are integrated with data from histological and radiological imaging, lifestyle, demographic characteristics, environmental and occupational exposures, and medical records to classify LCINS into subtypes that could reveal distinct risk factors. To date, we have received samples and data from 1,370 LCINS cases from 17 study sites worldwide and whole-genome sequencing has been completed on 1,257 samples. Here, we present the Sherlock-Lung study design and analytical strategy, also illustrating some empirical challenges and the potential for this approach in future epidemiologic studies.

A Spontaneous Aggressive ERα+ Mammary Tumor Model Is Driven by Kras Activation

The NRL-PRL murine model, defined by mammary-selective transgenic rat prolactin ligand rPrl expression, establishes spontaneous ER+ mammary tumors in nulliparous females, mimicking the association between elevated prolactin (PRL) and risk for development of ER+ breast cancer in postmenopausal women. Whole-genome and exome sequencing in a discovery cohort (n = 5) of end-stage tumors revealed canonical activating mutations and copy number amplifications of Kras. The frequent mutations in this pathway were validated in an extension cohort, identifying activating Ras alterations in 79% of tumors (23 of 29). Transcriptome analyses over the course of oncogenesis revealed marked alterations associated with Ras activity in established tumors compared with preneoplastic tissues; in cell-intrinsic processes associated with mitosis, cell adhesion, and invasion; as well as in the surrounding tumor environment. These genomic analyses suggest that PRL induces a selective bottleneck for spontaneous Ras-driven tumors that may model a subset of aggressive clinical ER+ breast cancers.

Integrative genomic analyses identify WDR12 as a novel oncogene involved in glioblastoma

Glioblastoma (GBM) is the most malignant primary brain tumor in adults. Due to its invasive nature, it cannot be thoroughly eliminated. WD repeat domain 12 (WDR12) processes the 32S precursor rRNA but cannot affect the synthesis of the 45S/47S primary transcript. In this study, we found that WDR12 is highly expressed in GBM according to the analysis results of mRNA expression by The Cancer Genome Atlas database. The high expression level of WDR12 is dramatically related to shorter overall survival and reduced disease-free survival. Next, we knocked down WDR12 and found that knockdown of WDR12 promoted the apoptosis and inhibited the proliferation by cell biology experiments. Differential expression genes in gene-chip revealed that WDR12 knockdown mainly inhibited cell cycle. Finally, we also found that WDR12 is associated with PLK1 and EZH2 in cell proliferation of GBM. Resumptively, this report showed a possible evidence that WDR12 drove malignant behavior of GBM, whose expression may present a neoteric independent prognostic biomarker in GBM.

Genomic analyses of multidrug resistant Pseudomonas aeruginosa PA1 resequenced by single-molecule real-time sequencing

As a third-generation sequencing (TGS) method, single-molecule real-time (SMRT) technology provides long read length, and it is well suited for resequencing projects and de novo assembly. In the present study, Pseudomonas aeruginosa PA1 was characterized and resequenced using SMRT technology. PA1 was also subjected to genomic, comparative and pan-genomic analyses. The multidrug resistant strain PA1 possesses a 6,498,072 bp genome and a sequence type of ST-782. The genome of PA1 was also visualized, and the results revealed the details of general genome annotations, virulence factors, regulatory proteins (RPs), secretion system proteins, type II toxin–antitoxin (T–A) pairs and genomic islands. Whole genome comparison analysis suggested that PA1 exhibits similarity to other P. aeruginosa strains but differs in terms of horizontal gene transfer (HGT) regions, such as prophages and genomic islands. Phylogenetic analyses based on 16S rRNA sequences demonstrated that PA1 is closely related to PAO1, and P. aeruginosa strains can be divided into two main groups. The pan-genome of P. aeruginosa consists of a core genome of approximately 4,000 genes and an accessory genome of at least 6,600 genes. The present study presented a detailed, visualized and comparative analysis of the PA1 genome, to enhance our understanding of this notorious pathogen.

A Brazilian Marseillevirus Is the Founding Member of a Lineage in Family Marseilleviridae

In 2003, Acanthamoeba polyphaga mimivirus (APMV) was discovered as parasitizing Acanthamoeba. It was revealed to exhibit remarkable features, especially odd genomic characteristics, and founded viral family Mimiviridae. Subsequently, a second family of giant amoebal viruses was described, Marseilleviridae, whose prototype member is Marseillevirus, discovered in 2009. Currently, the genomes of seven different members of this family have been fully sequenced. Previous phylogenetic analysis suggested the existence of three Marseilleviridae lineages: A, B and C. Here, we describe a new member of this family, Brazilian Marseillevirus (BrMV), which was isolated from a Brazilian sample and whose genome was fully sequenced and analyzed. Surprisingly, data from phylogenetic analyses and comparative genomics, including mean amino acid identity between BrMV and other Marseilleviridae members and the analyses of the core genome and pan-genome of marseilleviruses, indicated that this virus can be assigned to a new Marseilleviridae lineage. Even if the BrMV genome is one of the smallest among Marseilleviridae members, it harbors the second largest gene content into this family. In addition, the BrMV genome encodes 29 ORFans. Here, we describe the isolation and genome analyses of the BrMV strain, and propose its classification as the prototype virus of a new lineage D within the family Marseilleviridae.

Comparative genomic and genetic analysis of glioblastoma-derived brain tumor-initiating cells and their parent tumors

BACKGROUND

Glioblastoma (GBM) is a fatal cancer that has eluded major therapeutic advances. Failure to make progress may reflect the absence of a human GBM model that could be used to test compounds for anti-GBM activity. In this respect, the development of brain tumor-initiating cell (BTIC) cultures is a step forward because BTICs appear to capture the molecular diversity of GBM better than traditional glioma cell lines. Here, we perform a comparative genomic and genetic analysis of BTICs and their parent tumors as preliminary evaluation of the BTIC model.

METHODS

We assessed single nucleotide polymorphisms (SNPs), genome-wide copy number variations (CNVs), gene expression patterns, and molecular subtypes of 11 established BTIC lines and matched parent tumors.

RESULTS

Although CNV differences were noted, BTICs retained the major genomic alterations characteristic of GBM. SNP patterns were similar between BTICs and tumors. Importantly, recurring SNP or CNV alterations specific to BTICs were not seen. Comparative gene expression analysis and molecular subtyping revealed differences between BTICs and GBMs. These differences formed the basis of a 63-gene expression signature that distinguished cells from tumors; differentially expressed genes primarily involved metabolic processes. We also derived a set of 73 similarly expressed genes; these genes were not associated with specific biological functions.

CONCLUSIONS

Although not identical, established BTIC lines preserve the core molecular alterations seen in their parent tumors, as well as the genomic hallmarks of GBM, without acquiring recurring BTIC-specific changes.

Whole genome analyses of G1P[8] rotavirus strains from vaccinated and non-vaccinated South African children presenting with diarrhea

Group A rotaviruses (RVAs) are the leading cause of severe gastroenteritis and eventually death among infants and young children worldwide, and disease prevention and management through vaccination is a public health priority. In August 2009, Rotarix™ was introduced in the South African Expanded Programme on Immunisation. As a result, substantial reductions in RVA disease burden have been reported among children younger than 5 years old. Rotavirus strain surveillance post-vaccination is crucial to, inter alia, monitor and study the evolution of vaccine escape strains. Here, full-genome sequence data for the 11 gene segments from 11 South African G1P[8] rotavirus strains were generated, including 5 strains collected from non-vaccinated children during the 2004-2009 rotavirus seasons and 6 strains collected from vaccinated children during the 2010 rotavirus season. These data were analyzed to gain insights into the overall genetic makeup and evolution of South African G1P[8] rotavirus strains and to compare their genetic backbones with those of common human Wa-like RVAs from other countries, as well as with the Rotarix™ and RotaTeq™ G1P[8] vaccine components. All 11 South African G1P[8] strains revealed a complete Wa-like genotype constellation of G1-P[8]-I1-R1-C1-M1-A1-N1-T1-E1-H1. On the basis of sequence similarities, the South African G1P[8] strains (with the exception of strain RVA/Human-wt/ZAF/1262/2004/G1P[8]) were closely related to each other (96-100% identity in all gene segments). Comparison to the Rotarix™ and RotaTeq™ G1P[8] vaccine components revealed a moderate nucleotide identity of 89-96% and 93-95%, respectively. The results indicated that none of the gene segments of these 11 South African G1P[8] strains were vaccine-derived. This study illustrates that large-scale next generation sequencing will provide crucial information on the influence of the vaccination program on evolution of rotavirus strains. This is the first report to describe full genomic analyses of G1P[8] RVA strains collected from both non-vaccinated and vaccinated children in South Africa.

EvoPipes.net: Bioinformatic Tools for Ecological and Evolutionary Genomics

Recent increases in the production of genomic data are yielding new opportunities and challenges for biologists. Among the chief problems posed by next-generation sequencing are assembly and analyses of these large data sets. Here we present an online server, http://EvoPipes.net, that provides access to a wide range of tools for bioinformatic analyses of genomic data oriented for ecological and evolutionary biologists. The EvoPipes.net server includes a basic tool kit for analyses of genomic data including a next-generation sequence cleaning pipeline (SnoWhite), scaffolded assembly software (SCARF), a reciprocal best-blast hit ortholog pipeline (RBH Orthologs), a pipeline for reference protein-based translation and identification of reading frame in transcriptome and genomic DNA (TransPipe), a pipeline to identify gene families and summarize the history of gene duplications (DupPipe), and a tool for developing SSRs or microsatellites from a transcriptome or genomic coding sequence collection (findSSR). EvoPipes.net also provides links to other software developed for evolutionary and ecological genomics, including chromEvol and NU-IN, as well as a forum for discussions of issues relating to genomic analyses and interpretation of results. Overall, these applications provide a basic bioinformatic tool kit that will enable ecologists and evolutionary biologists with relatively little experience and computational resources to take advantage of the opportunities provided by next-generation sequencing in their systems.

Comparison between simulated annealing algorithms and rapid chain delineation in the construction of genetic maps

The efficiency of simulated annealing algorithms and rapid chain delineation in establishing the best linkage order, when constructing genetic maps, was evaluated. Linkage refers to the phenomenon by which two or more genes, or even more molecular markers, can be present in the same chromosome or linkage group. In order to evaluate the capacity of algorithms, four F₂ co-dominant populations, 50, 100, 200 and 1000 in size, were simulated. For each population, a genome with four linkage groups (100 cM) was generated. The linkage groups possessed 51, 21, 11 and 6 marks, respectively, and a corresponding distance of 2, 5, 10 and 20 cM between adjacent marks, thereby causing various degrees of saturation. For very saturated groups, with an adjacent distance between marks of 2 cM and in greater number, i.e., 51, the method based upon stochastic simulation by simulated annealing presented orders with distances equivalent to or lower than rapid chain delineation. Otherwise, the two methods were commensurate through presenting the same SARF distance.

Proteomic approaches for studying alcoholism and alcohol-induced organ damage

Proteomics research is concerned with the analysis of all proteins found in an organism, tissue, cell type, or cellular structure. The shotgun proteomic approach, which involves two-dimensional gel electrophoresis or liquid chromatography combined with mass spectrometry (MS), is used to identify novel proteins affected by alcohol. More targeted analyses study protein-protein interactions using such techniques as the yeast two-hybrid system, affinity chromatography, or immunoprecipitation. Finally, proteomic strategies can be combined with genomic research findings using computer analyses (i.e., in silico). All of these approaches have been used in the alcohol field. These studies have identified proteins in various brain regions whose expression is affected by alcohol. Other investigators have used proteomic approaches to identify proteins that could serve as potential biomarkers of alcohol use. Finally, interaction proteomic analyses have begun to identify proteins involved in several nerve signaling networks in the brain, which then can serve as targets for further studies on alcohol's effects. Future proteomic studies likely will shed more light on the mechanisms underlying alcohol's actions on the body.