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At least 127 records · Page 7

Footprints of Worldwide Adaptation in Structured Populations of Drosophila melanogaster Through the Expanded DEST 2.0 Genomic Resource

Abstract Large-scale genomic resources can place genetic variation into an ecologically informed context. To advance our understanding of the population genetics of the fruit fly Drosophila melanogaster, we present an expanded release of the community-generated population genomics resource Drosophila Evolution over Space and Time (DEST 2.0; https://dest.bio/). This release includes 530 high-quality pooled libraries from flies collected across six continents over more than a decade (2009 to 2021), most at multiple time points per year; 211 of these libraries are sequenced and shared here for the first time. We used this enhanced resource to elucidate several aspects of the species' demographic history and identify novel signs of adaptation across spatial and temporal dimensions. For example, we showed that the spatial genetic structure of populations is stable over time, but that drift due to seasonal contractions of population size causes populations to diverge over time. We identified signals of adaptation that vary between continents in genomic regions associated with xenobiotic resistance, consistent with independent adaptation to common pesticides. Moreover, by analyzing samples collected during spring and fall across Europe, we provide new evidence for seasonal adaptation related to loci associated with pathogen response. Furthermore, we have also released an updated version of the DEST genome browser. This is a useful tool for studying spatiotemporal patterns of genetic variation in this classic model system.

Biochemistry & Molecular Biology

Automated Miniaturized Instrument for Space Biology Applications and the Monitoring of the Astronauts Health Onboard the ISS

Human space travelers experience a unique environment that affects homeostasis and physiologic adaptation. The spacecraft environment subjects the traveler to noise, chemical and microbiological contaminants, increased radiation, and variable gravity forces. As humans prepare for long-duration missions to the International Space Station (ISS) and beyond, effective measures must be developed, verified and implemented to ensure mission success. Limited biomedical quantitative capabilities are currently available onboard the ISS. Therefore, the development of versatile instruments to perform space biological analysis and to monitor astronauts' health is needed. We are developing a fully automated, miniaturized system for measuring gene expression on small spacecraft in order to better understand the influence of the space environment on biological systems. This low-cost, low-power, multi-purpose instrument represents a major scientific and technological advancement by providing data on cellular metabolism and regulation. The current system will support growth of microorganisms, extract and purify the RNA, hybridize it to the array, read the expression levels of a large number of genes by microarray analysis, and transmit the measurements to Earth. The system will help discover how bacteria develop resistance to antibiotics and how pathogenic bacteria sometimes increase their virulence in space, facilitating the development of adequate countermeasures to decrease risks associated with human spaceflight. The current stand-alone technology could be used as an integrated platform onboard the ISS to perform similar genetic analyses on any biological systems from the tree of life. Additionally, with some modification the system could be implemented to perform real-time in-situ microbial monitoring of the ISS environment (air, surface and water samples) and the astronaut's microbiome using 16SrRNA microarray technology. Furthermore, the current system can be enhanced substantially by combining it with other technologies for automated, miniaturized, high-throughput biological measurements, such as fast sequencing, protein identification (proteomics) and metabolite profiling (metabolomics). Thus, the system can be integrated with other biomedical instruments in order to support and enhance telemedicine capability onboard ISS. NASA's mission includes sustained investment in critical research leading to effective countermeasures to minimize the risks associated with human spaceflight, and the use of appropriate technology to sustain space exploration at reasonable cost. Our integrated microarray technology is expected to fulfill these two critical requirements and to enable the scientific community to better understand and monitor the effects of the space environment on microorganisms and on the astronaut, in the process leveraging current capabilities and overcoming present limitations.

Human space travelers

Standardized Residue Numbering and Secondary Structure Nomenclature in the Class D β-Lactamases

Over 1370 class D β-lactamases are currently known, and they pose a serious threat to the effective treatment of many infectious diseases, particularly in some pathogenic bacteria where evolving carbapenemase activity has been reported. Detailed understanding of their molecular biology, enzymology, and structural biology are critically important, but the lack of a standardized residue numbering scheme and inconsistent secondary structure annotation has made comparative analyses sometimes difficult and cumbersome. Compounding this, in the post-AlphaFold world where we currently find ourselves, an extraordinary wealth of detailed structural information on these enzymes is literally at our fingertips; therefore it is vitally important that a standard numbering system is in place to facilitate the accurate and straightforward analysis of their structures. In conclusion, here we present a residue numbering and secondary structure scheme for the class D enzymes based on the sequence and structure of OXA-48 and apply it to test targets to demonstrate the ease with which it can be used.

59 BASIC BIOLOGICAL SCIENCES

Real-time PCR assays that detect genes for botulinum neurotoxin A–G subtypes

The role of Real-Time PCR assays for surveillance and rapid screening for pathogens is garnering more and more attention because of its versatility and ease of adoption. The goal of this study was to design, test, and evaluate Real-Time TaqMan PCR assays for the detection of botulinum neurotoxin (bont/A-G) genes from currently recognized BoNT subtypes. Assays were computationally designed and then laboratory tested for sensitivity and specificity using DNA preparations containing bont genes from 82 target toxin subtypes, including nine bivalent toxin types; 31 strains representing other clostridial species; and an extensive panel that consisted of DNA from a diverse set of prokaryotic (bacterial) and eukaryotic (fungal, protozoan, plant, and animal) species. In addition to laboratory testing, the assays were computationally evaluated using in silico analysis for their ability to detect bont gene sequences from recently identified toxin subtypes. Seventeen specific assays (two for each of the bont/C, bont/D, bont/E, and bont/G subtypes and three for each of the bont/A, bont/B, and bont/F subtypes) were designed and evaluated for their ability to detect bont genes encoding multiple subtypes from all seven serotypes. These assays could provide an additional tool for the detection of botulinum neurotoxins in clinical, environmental and food samples that can complement other existing methods used in clinical diagnostics, regulatory, public health, and research laboratories.

59 BASIC BIOLOGICAL SCIENCES

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Zishuo Zeng

Machine learning identifies novel signatures of antifungal drug resistance in Saccharomycotina yeasts

Antifungal drug resistance is a major challenge in fungal infection management. Numerous genomic changes are known to contribute to acquired drug resistance in clinical isolates of specific pathogens, but whether they broadly explain natural resistance across entire lineages is unknown. We leveraged genomic, ecological, and phenotypic trait data from naturally sampled strains from nearly all known species in subphylum Saccharomycotina to examine the evolution of resistance to eight antifungal drugs. The phylogenetic distribution of drug resistance varied by drug; fluconazole resistance was widespread, while 5-fluorocytosine resistance was rare, except in Lipomycetales. A random forest algorithm trained on genomic data predicted drug-resistant yeasts with 54–75% accuracy. Fluconazole resistance was consistently predicted with the highest accuracy (75.2%). Furthermore, fluconazole resistance prediction accuracy was similar between models trained on genome-wide variation in the presence and number of InterPro protein annotations across Saccharomycotina (75.2%) and those trained on amino acid sequence alignment data of Erg11, a protein known to be involved in fluconazole resistance (74.3-74.9%). Interestingly, the top Erg11 residues for predicting fluconazole resistance across Saccharomycotina do not overlap with, are not spatially close to, and are less conserved than those previously linked to resistance in clinical isolates of Candida albicans. In silico deep mutational scanning of the C. albicans Erg11 protein reveals that amino acid variants implicated in clinical cases of resistance are almost universally destabilizing while variants in our most informative residues are energetically more neutral, explaining why the latter are much more common than the former in natural populations. Importantly, previous experimental analyses of C. albicans Erg11 have shown that amino acid variation in our most informative residues, despite having never been directly implicated in clinical cases, can directly contribute to resistance. Our results suggest that studies of natural resistance in yeast species never encountered in the clinic will yield a fuller understanding of antifungal drug resistance.

Harrison, Marie-Claire [Vanderbilt Univ., Nashvill

A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders

Abstract Unsolved Mendelian cases often lack obvious pathogenic coding variants, suggesting potential non-coding etiologies. Here, we present a single cell multi-omic framework integrating embryonic mouse chromatin accessibility, histone modification, and gene expression assays to discover cranial motor neuron (cMN)cis-regulatory elements and subsequently nominate candidate non-coding variants in the congenital cranial dysinnervation disorders (CCDDs), a set of Mendelian disorders altering cMN development. We generate single cell epigenomic profiles for ~86,000 cMNs and related cell types, identifying ~250,000 accessible regulatory elements with cognate gene predictions for ~145,000 putative enhancers. We evaluate enhancer activity for 59 elements using an in vivo transgenic assay and validate 44 (75%), demonstrating that single cell accessibility can be a strong predictor of enhancer activity. Applying our cMN atlas to 899 whole genome sequences from 270 genetically unsolved CCDD pedigrees, we achieve significant reduction in our variant search space and nominate candidate variants predicted to regulate known CCDD disease genesMAFB, PHOX2A, CHN1, andEBF3– as well as candidates in recurrently mutated enhancers through peak- and gene-centric allelic aggregation. This work delivers non-coding variant discoveries of relevance to CCDDs and a generalizable framework for nominating non-coding variants of potentially high functional impact in other Mendelian disorders.

Science & Technology - Other Topics

Transfer of beef bacterial communities onto food-contact surfaces

Introduction Food spoilage and pathogenic bacteria on food-contact surfaces, especially biofilm-forming strains, can transfer to meats during processing. The objectives of this study were to survey the bacterial communities of beef cuts that transfer onto two commonly used food-contact surfaces, stainless steel (SS) and high-density polyethylene (HDPE) and identify potentially biofilm-forming strains. Methods Top round, flank, chuck, and ground beef were purchased from 3 retail stores. SS and HDPE coupons (approximately 2cm × 5cm) were placed on beef portions (3h, 10°C), after which, the coupons were submerged halfway in PBS (24h, 10°C). Bacteria from the beef cuts and coupon surfaces ( n = 3) were collected, plated on tryptic soy agar plates and incubated (5 days, 25°C). Bacterial isolates were identified by 16S rRNA gene amplicon sequencing and assayed for biofilm formation using a crystal violet binding (CV) assay (72h, 10°C). Additionally, beef and coupon samples were collected for bacterial community analysis by 16S rRNA gene amplicon sequencing. Results and discussion Sixty-one of 972 beef isolates, 29 of 204 HDPE isolates, and 30 of 211 SS isolates were strong biofilm-formers (Absorbance>1.000 at 590 nm in the CV assay). Strong-binding isolates identified were of the genera Pseudomonas , Acinetobacter , Psychrobacter , Carnobacterium , and Brochothrix . Coupon bacterial communities among stores and cuts were distinct ( p < 0.001, PERMANOVA), but there was no distinction between the communities found on HDPE or SS coupons ( p > 0.050, PERMANOVA). The bacterial communities identified on the coupons may help determine the communities capable of transferring and colonizing onto surfaces, which can subsequently cross-contaminate foods.

Guron, Giselle K. P.

CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting

With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.

60 APPLIED LIFE SCIENCES

Isolation and characterization of IgG3 glycan-targeting antibodies with exceptional cross-reactivity for diverse viral families

Broadly reactive antibodies that target sequence-diverse antigens are of interest for vaccine design and monoclonal antibody therapeutic development because they can protect against multiple strains of a virus and provide a barrier to evolution of escape mutants. Using LIBRA-seq (linking B cell receptor to antigen specificity through sequencing) data for the B cell repertoire of an individual chronically infected with human immunodeficiency virus type 1 (HIV-1), we identified a lineage of IgG3 antibodies predicted to bind to HIV-1 Envelope (Env) and influenza A Hemagglutinin (HA). Two lineage members, antibodies 2526 and 546, were confirmed to bind to a large panel of diverse antigens, including several strains of HIV-1 Env, influenza HA, coronavirus (CoV) spike, hepatitis C virus (HCV) E protein, Nipah virus (NiV) F protein, and Langya virus (LayV) F protein. We found that both antibodies bind to complex glycans on the antigenic surfaces. Antibody 2526 targets the stem region of influenza HA and the N-terminal domain (NTD) region of SARS-CoV-2 spike. A crystal structure of 2526 Fab bound to mannose revealed the presence of a glycan-binding pocket on the light chain. Antibody 2526 cross-reacted with antigens from multiple pathogens and displayed no signs of autoreactivity. These features distinguish antibody 2526 from previously described glycan-reactive antibodies. Further study of this antibody class may aid in the selection and engineering of broadly reactive antibody therapeutics and can inform the development of effective vaccines with exceptional breadth of pathogen coverage.

Microbiology

Host population dynamics influence Leptospira spp. transmission patterns among Rattus norvegicus in Boston, Massachusetts, US

Leptospirosis (caused by pathogenic bacteria in the genus Leptospira ) is prevalent worldwide but more common in tropical and subtropical regions. Transmission can occur following direct exposure to infected urine from reservoir hosts, or a urine-contaminated environment, which then can serve as an infection source for additional rats and other mammals, including humans. The brown rat, Rattus norvegicus , is an important reservoir of Leptospira spp. in urban settings. We investigated the presence of Leptospira spp. among brown rats in Boston, Massachusetts and hypothesized that rat population dynamics in this urban setting influence the transportation, persistence, and diversity of Leptospira spp. We analyzed DNA from 328 rat kidney samples collected from 17 sites in Boston over a seven-year period (2016–2022); 59 rats representing 12 of 17 sites were positive for Leptospira spp. We used 21 neutral microsatellite loci to genotype 311 rats and utilized the resulting data to investigate genetic connectivity among sampling sites. We generated whole genome sequences for 28 Leptospira spp. isolates obtained from frozen and fresh tissue from some of the 59 positive rat kidneys. When isolates were not obtained, we attempted genomic DNA capture and enrichment, which yielded 14 additional Leptospira spp. genomes from rats. We also generated an enriched Leptospira spp. genome from a 2018 human case in Boston. We found evidence of high genetic structure among rat populations that is likely influenced by major roads and/or other dispersal barriers, resulting in distinct rat population groups within the city; at certain sites these groups persisted for multiple years. We identified multiple distinct phylogenetic clades of L. interrogans among rats that were tightly linked to distinct rat populations. This pattern suggests L. interrogans persists in local rat populations and its transportation is influenced by rat population dynamics. Finally, our genomic analyses of the Leptospira spp. detected in the 2018 human leptospirosis case in Boston suggests a link to rats as the source. These findings will be useful for guiding rat control and human leptospirosis mitigation efforts in this and other similar urban settings.

Stone, Nathan E.

Mass Spectrometric Determination of Site-Specific O -Acetylation in Rhamnogalacturonan I Oligomers

O-acetylation, a common modification in rhamnogalacturonan I (RG-I), is critical for various biological processes, including plant growth, stress responses, and pathogen defense. Precise determination of the degree and specific positions of acetylation is therefore essential. To date, nuclear magnetic resonance (NMR) and tandem mass spectrometry have been employed to identify O-acetyl positions in pectin oligosaccharides. Although NMR is effective, it requires pure, high-concentration samples. Tandem mass spectrometry (MS), which uses smaller sample amounts, faces challenges due to O-acetyl migration between monosaccharide positions. The multiple steps in pectin sample analysis can further promote O-acetyl migration, especially near free hydroxyl groups. Moreover, during tandem MS, O-acetyl groups may detach, complicating the accurate tracking. This study presents an approach to lock O-acetyl groups by introducing trideuteroacetyl and propionyl substituents onto free hydroxyls of RG-I or partially acetylated RG-I. By combining matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS and electrospray ionization (ESI) MS with MS/MS or tandem mass spectrometry (MSn), we devised a way to determine the monosaccharide sequence in the oligomer and the precise positions of O-acetyl groups in partially acetylated RG-I. This method enables the study of the regiospecificity of recombinant pectin O-acetyltransferases and can be applied to other oligosaccharides to determine acyl positions.

O-acetylation

Host tracheal and intestinal microbiomes inhibit Coccidioides growth in vitro

Coccidioidomycosis, also known as Valley fever, is a disease caused by the fungal pathogen Coccidioides. Unfortunately, patients are often misdiagnosed with bacterial pneumonia, leading to inappropriate antibiotic treatment. The soil Bacillus subtilis-like species exhibits antagonistic properties against Coccidioides in vitro; however, the antagonistic capabilities of host microbiota against Coccidioides are unexplored. We sought to examine the potential of the tracheal and intestinal microbiomes to inhibit the growth of Coccidioides in vitro. We hypothesized that an uninterrupted lawn of microbiota obtained from antibiotic-free mice would inhibit the growth of Coccidioides, while partial in vitro depletion through antibiotic disk diffusion assays would allow a niche for fungal growth. We observed that the microbiota grown on 2×GYE (GYE) and Columbia colistin and nalidixic acid with 5% sheep’s blood agar inhibited the growth of Coccidioides, but microbiota grown on chocolate agar did not. Partial depletion of the microbiota through antibiotic disk diffusion revealed diminished inhibition and comparable growth of Coccidioides to controls. To characterize the bacteria grown and identify potential candidates contributing to the inhibition of Coccidioides, 16S rRNA sequencing was performed on tracheal and intestinal agar cultures and murine lung extracts. We found that the host bacteria likely responsible for this inhibition primarily included Lactobacillus and Staphylococcus. The results of this study demonstrate the potential of the host microbiota to inhibit the growth of Coccidioides in vitro and suggest that an altered microbiome through antibiotic treatment could negatively impact effective fungal clearance and allow a niche for fungal growth in vivo.

59 BASIC BIOLOGICAL SCIENCES

Vascular defense responses in rice: peroxidase accumulation in xylem parenchyma cells and xylem wall thickening

The rice bacterial blight pathogen Xanthomonas oryzae pv. oryzae is a vascular pathogen that elicits a defensive response through interaction with metabolically active rice cells. In leaves of 12-day-old rice seedlings, the exposed pit membrane separating the xylem lumen from the associated parenchyma cells allows contact with bacterial cells. During resistant responses, the xylem secondary walls thicken within 48 h and the pit diameter decreases, effectively reducing the area of pit membrane exposed for access by bacteria. In susceptible interactions and mock-inoculated controls, the xylem walls do not thicken within 48 h. Xylem secondary wall thickening is developmental and, in untreated 65-day-old rice plants, the size of the pit also is reduced. Activity and accumulation of a secreted cationic peroxidase, PO-C1, were previously shown to increase in xylem vessel walls and lumen. Peptide-specific antibodies and immunogold-labeling were used to demonstrate that PO-C1 is produced in the xylem parenchyma and secreted to the xylem lumen and walls. The timing of the accumulation is consistent with vessel secondary wall thickening. The PO-C1 gene is distinct but shares a high level of similarity with previously cloned pathogen-induced peroxidases in rice. PO-C1 gene expression was induced as early as 12 h during resistant interactions and peaked between 18 and 24 h after inoculation. Expression during susceptible interactions was lower than that observed in resistant interactions and was undetectable after infiltration with water, after mechanical wounding, or in mature leaves. These data are consistent with a role for vessel secondary wall thickening and peroxidase PO-C1 accumulation in the defense response in rice to X. oryzae pv. oryzae.

NASA Discipline Plant Biology

Mutations in the dopamine beta-hydroxylase gene are associated with human norepinephrine deficiency

Norepinephrine (NE), a key neurotransmitter of the central and peripheral nervous systems, is synthesized by dopamine beta-hydroxylase (DBH) that catalyzes oxidation of dopamine (DA) to NE. NE deficiency is a congenital disorder of unknown etiology, in which affected patients suffer profound autonomic failure. Biochemical features of the syndrome include undetectable tissue and circulating levels of NE and epinephrine, elevated levels of DA, and undetectable levels of DBH. Here, we report identification of seven novel variants including four potentially pathogenic mutations in the human DBH gene (OMIM 223360) from analysis of two unrelated patients and their families. Both patients are compound heterozygotes for variants affecting expression of DBH protein. Each carries one copy of a T-->C transversion in the splice donor site of DBH intron 1, creating a premature stop codon. In patient 1, there is a missense mutation in DBH exon 2. Patient 2 carries missense mutations in exons 1 and 6 residing in cis. We propose that NE deficiency is an autosomal recessive disorder resulting from heterogeneous molecular lesions at DBH. Copyright 2002 Wiley-Liss, Inc.

Case Reports

Identification of a dual-specificity protein phosphatase that inactivates a MAP kinase from Arabidopsis

Mitogen-activated protein kinases (MAPKs) play a key role in plant responses to stress and pathogens. Activation and inactivation of MAPKs involve phosphorylation and dephosphorylation on both threonine and tyrosine residues in the kinase domain. Here we report the identification of an Arabidopsis gene encoding a dual-specificity protein phosphatase capable of hydrolysing both phosphoserine/threonine and phosphotyrosine in protein substrates. This enzyme, designated AtDsPTP1 (Arabidopsis thaliana dual-specificity protein tyrosine phosphatase), dephosphorylated and inactivated AtMPK4, a MAPK member from the same plant. Replacement of a highly conserved cysteine by serine abolished phosphatase activity of AtDsPTP1, indicating a conserved catalytic mechanism of dual-specificity protein phosphatases from all eukaryotes.

Non-NASA Center

Cell and molecular biology of simian virus 40: implications for human infections and disease

Simian virus 40 (SV40), a polyomavirus of rhesus macaque origin, was discovered in 1960 as a contaminant of polio vaccines that were distributed to millions of people from 1955 through early 1963. SV40 is a potent DNA tumor virus that induces tumors in rodents and transforms many types of cells in culture, including those of human origin. This virus has been a favored laboratory model for mechanistic studies of molecular processes in eukaryotic cells and of cellular transformation. The viral replication protein, named large T antigen (T-ag), is also the viral oncoprotein. There is a single serotype of SV40, but multiple strains of virus exist that are distinguishable by nucleotide differences in the regulatory region of the viral genome and in the part of the T-ag gene that encodes the protein's carboxyl terminus. Natural infections in monkeys by SV40 are usually benign but may become pathogenic in immunocompromised animals, and multiple tissues can be infected. SV40 can replicate in certain types of simian and human cells. SV40-neutralizing antibodies have been detected in individuals not exposed to contaminated polio vaccines. SV40 DNA has been identified in some normal human tissues, and there are accumulating reports of detection of SV40 DNA and/or T-ag in a variety of human tumors. This review presents aspects of replication and cell transformation by SV40 and considers their implications for human infections and disease pathogenesis by the virus. Critical assessment of virologic and epidemiologic data suggests a probable causative role for SV40 in certain human cancers, but additional studies are necessary to prove etiology.

Review

Hydrogen peroxide homeostasis: activation of plant catalase by calcium/calmodulin

Environmental stimuli such as UV, pathogen attack, and gravity can induce rapid changes in hydrogen peroxide (H(2)O(2)) levels, leading to a variety of physiological responses in plants. Catalase, which is involved in the degradation of H(2)O(2) into water and oxygen, is the major H(2)O(2)-scavenging enzyme in all aerobic organisms. A close interaction exists between intracellular H(2)O(2) and cytosolic calcium in response to biotic and abiotic stresses. Studies indicate that an increase in cytosolic calcium boosts the generation of H(2)O(2). Here we report that calmodulin (CaM), a ubiquitous calcium-binding protein, binds to and activates some plant catalases in the presence of calcium, but calcium/CaM does not have any effect on bacterial, fungal, bovine, or human catalase. These results document that calcium/CaM can down-regulate H(2)O(2) levels in plants by stimulating the catalytic activity of plant catalase. Furthermore, these results provide evidence indicating that calcium has dual functions in regulating H(2)O(2) homeostasis, which in turn influences redox signaling in response to environmental signals in plants.

NASA Discipline Plant Biology