New technologies to assess genotype-phenotype relationships

Characteristics of Corynespora cassiicola, the causal agent of tobacco Corynespora leaf spot, revealed by genomic and metabolic phenomic analysis

Corynespora cassiicola is a highly diverse fungal pathogen that commonly occurs in tropical, subtropical, and greenhouse environments worldwide. In this study, the isolates were identified as C. cassiicola, and the optimum growth and sporulation were studied. The phenotypic characteristics of C. cassiicola, concerning 950 different growth conditions, were tested using Biolog PM plates 1-10. In addition, the strain of C. cassiicola DWZ from tobacco hosts was sequenced for the using Illumina PE150 and Pacbio technologies. The host resistance of tobacco Yunyan 87 with different maturity levels was investigated. In addition, the resistance evaluation of 10 common tobacco varieties was investigated. The results showed that C. cassiicola metabolized 89.47% of the tested carbon source, 100% of the nitrogen source, 100% of the phosphorus source, and 97.14% of the sulfur source. It can adapt to a variety of different osmotic pressure and pH environments, and has good decarboxylase and deaminase activities. The optimum conditions for pathogen growth and sporulation were 25-30 °C, and the growth was better on AEA and OA medium. The total length of the genome was 45.9 Mbp, the GC content was 51.23%, and a total of 13,061 protein-coding genes, 202 non-coding RNAs and 2801 and repeat sequences were predicted. Mature leaves were more susceptible than proper mature and immature leaves, and the average diameter of diseased spots reached 17.74 mm at 12 days. None of the tested ten cultivars exhibited obvious resistance to Corynespora leaf spot of tobacco, whereby all disease spot diameters reached > 10 mm and > 30 mm when at 5 and 10 days after inoculation, respectively. The phenotypic characteristics, genomic analysis of C. cassiicola and the cultivar resistance assessment of this pathogen have increased our understanding of Corynespora leaf spot of tobacco.

Biological characteristics and metabolic phenotypes of different anastomosis groups of Rhizoctonia solani strains

BACKGROUND

Rhizoctonia solani is an important plant pathogen worldwide, and causes serious tobacco target spot in tobacco in the last five years. This research studied the biological characteristics of four different anastomosis groups strains (AG-3, AG-5, AG-6, AG-1-IB) of R. solani from tobacco. Using metabolic phenotype technology analyzed the metabolic phenotype differences of these strains.

RESULTS

The results showed that the suitable temperature for mycelial growth of four anastomosis group strains were from 20 to 30oC, and for sclerotia formation were from 20 to 25oC. Under different lighting conditions, R. solani AG-6 strains produced the most sclerotium, followed by R. solani AG-3, R. solani AG-5 and R. solani AG-1-IB. All strains had strong oligotrophic survivability, and can grow on water agar medium without any nitrutions. They exhibited three types of sclerotia distribution form, including dispersed type (R. solani AG-5 and AG-6), peripheral type (R. solani AG-1-IB), and central type (R. solani AG-3). They all presented different pathogenicities in tobacco leaves, with the most virulent was noted by R. solani AG-6, followed by R. solani AG-5 and AG-1-IB, finally was R. solani AG-3. R. solani AG-1-IB strains firstly present symptom after inoculation. Metabolic fingerprints of four anastomosis groups were different to each other. R. solani AG-3, AG-6, AG-5 and AG-1-IB strains efficiently metabolized 88, 94, 71 and 92 carbon substrates, respectively. Nitrogen substrates of amino acids and peptides were the significant utilization patterns for R. solani AG-3. R. solani AG-3 and AG-6 showed a large range of adaptabilities and were still able to metabolize substrates in the presence of the osmolytes, including up to 8% sodium lactate. Four anastomosis groups all showed active metabolism in environments with pH values from 4 to 6 and exhibited decarboxylase activities.

CONCLUSIONS

The biological characteristics of different anastomosis group strains varies, and there were significant differences in the metabolic phenotype characteristics of different anastomosis group strains towards carbon source, nitrogen source, pH, and osmotic pressure.

Profiling the compendium of changes in Saccharomyces cerevisiae due to mutations that alter availability of the main methyl donor S-Adenosylmethionine

The SAM1 and SAM2 genes encode for S-Adenosylmethionine (AdoMet) synthetase enzymes, with AdoMet serving as the main cellular methyl donor. We have previously shown that independent deletion of these genes alters chromosome stability and AdoMet concentrations in opposite ways in Saccharomyces cerevisiae. To characterize other changes occurring in these mutants, we grew wildtype, sam1Δ/sam1Δ, and sam2Δ/sam2Δ strains in 15 different Phenotypic Microarray plates with different components and measured growth variations. RNA-Sequencing was also carried out on these strains and differential gene expression determined for each mutant. We explored how the phenotypic growth differences are linked to the altered gene expression, and hypothesize mechanisms by which loss of the SAM genes and subsequent AdoMet level changes, impact pathways and processes. We present 6 stories, discussing changes in sensitivity or resistance to azoles, cisplatin, oxidative stress, arginine biosynthesis perturbations, DNA synthesis inhibitors, and tamoxifen, to demonstrate the power of this novel methodology to broadly profile changes due to gene mutations. The large number of conditions that result in altered growth, as well as the large number of differentially expressed genes with wide-ranging functionality, speaks to the broad array of impacts that altering methyl donor abundance can impart. Our findings demonstrate that some cellular changes are directly related to AdoMet-dependent methyltransferases and AdoMet availability, some are directly linked to the methyl cycle and its role in production of several important cellular components, and others reveal impacts of SAM gene mutations on previously unconnected pathways.

High-quality genome assembly and genetic transformation system of Lasiodiplodia theobromae strain LTTK16-3, a fungal pathogen of Chinese hickory

Lasiodiplodia theobromae, as one of the causative agents associated with Chinese hickory trunk cankers, has caused huge economic losses to the Chinese hickory industry. Although the biological characteristics of this pathogen and the occurrence pattern of this disease have been well studied, few studies have addressed the related mechanisms due to the poor molecular and genetic study basis of this fungus. In this study, we sequenced and assembled L. theobromae strain LTTK16-3, isolated from a Chinese hickory tree (cultivar of Linan) in Linan, Zhejiang province, China. Phylogenetic analysis and comparative genomics analysis presented crucial cues in the prediction of LTTK16-3, which shared similar regulatory mechanisms of transcription, DNA replication, and DNA damage response with the other four Chinese hickory trunk canker-associated Botryosphaeria strains including, Botryosphaeria dothidea, Botryosphaeria fabicerciana, Botryosphaeria qingyuanensis, and Botryosphaeria corticis. Moreover, it contained 18 strain-specific protein clusters (not conserved in the other L. theobromae strains, AM2As and CITRA15), with potential roles in specific host-pathogen interactions during the Chinese hickory infection. Additionally, an efficient system for L. theobromae protoplast preparation and polyethylene glycol (PEG) -mediated genetic transformation was firstly established as the foundation for its future mechanisms study. Collectively, the high-quality genome data and the efficient transformation system of L. theobromae here set up the possibility of targeted molecular improvements for Chinese hickory canker control.IMPORTANCEFungi with disparate genomic features are physiologically diverse, possessing species-specific survival strategies and environmental adaptation mechanisms. The high-quality genome data and related molecular genetic studies are the basis for revealing the mechanisms behind the physiological traits that are responsible for their environmental fitness. In this study, we sequenced and assembled the LTTK16-3 strain, the genome of Lasiodiplodia theobromae first obtained from a diseased Chinese hickory tree (cultivar of Linan) in Linan, Zhejiang province, China. Further phylogenetic analysis and comparative genomics analysis provide crucial cues in the prediction of the proteins with potential roles in specific host-pathogen interactions during the Chinese hickory infection. An efficient PEG-mediated genetic transformation system of L. theobromae was established as the foundation for the future mechanisms exploration. The above genetic information and tools set up valuable clues to study L. theobromae pathogenesis and assist in Chinese hickory canker control.

Analysis of growth dynamics in five different media and metabolic phenotypic characteristics of Piriformospora indica

Piriformospora indica is an important endophytic fungus with broad potential for alleviating biotic and abiotic stress on host plants. This study monitored the growth dynamics of P. indica on five commonly used artificial media for microorganisms and analyzed its metabolic characteristics using Biolog Phenotype Microarray (PM) technology. The results showed that P. indica grew fastest on Potato Dextrose Agar (PDA), followed by Kidney Bean Agar (KBA), Alkyl Ester Agar (AEA), Oatmeal Agar (OA), and Luria-Bertani Agar (LB), and the most suitable medium for spore production was OA. Using Biolog PM1-10, 950 metabolic phenotypes of P. indica were obtained. P. indica could metabolize 87.89% of the tested carbon sources, 87.63% of the tested nitrogen sources, 96.61% of the tested phosphorus sources, and 100% of the tested sulfur sources. P. indica displayed 92 kinds of tested biosynthetic pathways, and it could grow under 92 kinds of tested osmotic pressures and 88 kinds of tested pH conditions. PM plates 1-2 revealed 43 efficient carbon sources, including M-Hydroxyphenyl acid, N-Acetyl-D-Glucosamine, Tyramine, Maltotrios, α-D-Glucosine, I-Erythritol, L-Valine, D-Melezitose, D-Tagatose, and Turanose. PM plates 3,6-8 indicated 170 efficient nitrogen sources, including Adenosine, Inosine Allantoin, D, L-Lactamide, Arg-Met, lle-Trp, Ala-Arg, Thr-Arg, Trp-Tyr, Val-Asn, Gly-Gly-D-Leu, Gly-Gly-Phe, and Leu-Leu-Leu. This study demonstrates that P. indica can metabolize a variety of substrates, such as carbon and nitrogen sources, and has a wide range of environmental adaptability. The growth dynamics on artificial culture media and metabolic phenotypes of P. indica can be used to investigate its biological characteristics, screen for more suitable growth and sporulation conditions, and elucidate the physiological mechanisms that enhance the stress resistance of host plants. This study provides a theoretical basis for its better application in agriculture.

Arabinose Plays an Important Role in Regulating the Growth and Sporulation of Bacillus subtilis NCD-2

A microbial fungicide developed from Bacillus subtilis NCD-2 has been registered for suppressing verticillium wilt in crops in China. Spores are the main ingredient of this fungicide and play a crucial role in suppressing plant disease. Therefore, increasing the number of spores of strain NCD-2 during fermentation is important for reducing the cost of the fungicide. In this study, five kinds of carbon sources were found to promote the metabolism of strain NCD-2 revealed via Biolog Phenotype MicroArray (PM) technology. L-arabinose showed the strongest ability to promote the growth and sporulation of strain NCD-2. L-arabinose increased the bacterial concentration and the sporulation efficiency of strain NCD-2 by 2.04 times and 1.99 times compared with D-glucose, respectively. Moreover, L-arabinose significantly decreased the autolysis of strain NCD-2. Genes associated with arabinose metabolism, sporulation, spore resistance to heat, and spore coat formation were significantly up-regulated, and genes associated with sporulation-delaying protein were significantly down-regulated under L-arabinose treatment. The deletion of msmX, which is involved in arabinose transport in the Bacillus genus, decreased growth and sporulation by 53.71% and 86.46% compared with wild-type strain NCD-2, respectively. Complementing the mutant strain by importing an intact msmX gene restored the strain's growth and sporulation.

Integrated genomics and phenotype microarray analysis of Saccharomyces cerevisiae industrial strains for rice wine fermentation and recombinant protein production

The industrial potential of Saccharomyces cerevisiae has extended beyond its traditional use in fermentation to various applications, including recombinant protein production. Herein, comparative genomics was performed with three industrial S. cerevisiae strains and revealed a heterozygous diploid genome for the 98-5 and KSD-YC strains (exploited for rice wine fermentation) and a haploid genome for strain Y2805 (used for recombinant protein production). Phylogenomic analysis indicated that Y2805 was closely associated with the reference strain S288C, whereas KSD-YC and 98-5 were grouped with Asian and European wine strains, respectively. Particularly, a single nucleotide polymorphism (SNP) in FDC1, involved in the biosynthesis of 4-vinylguaiacol (4-VG, a phenolic compound with a clove-like aroma), was found in KSD-YC, consistent with its lack of 4-VG production. Phenotype microarray (PM) analysis showed that KSD-YC and 98-5 displayed broader substrate utilization than S288C and Y2805. The SNPs detected by genome comparison were mapped to the genes responsible for the observed phenotypic differences. In addition, detailed information on the structural organization of Y2805 selection markers was validated by Sanger sequencing. Integrated genomics and PM analysis elucidated the evolutionary history and genetic diversity of industrial S. cerevisiae strains, providing a platform to improve fermentation processes and genetic manipulation.

Characteristics of Epicoccum latusicollum as revealed by genomic and metabolic phenomic analysis, the causal agent of tobacco Epicoccus leaf spot

Epicoccum latusicollum is a fungus that causes a severe foliar disease on flue-cured tobacco in southwest China, resulting in significant losses in tobacco yield and quality. To better understand the organism, researchers investigated its optimal growth conditions and metabolic versatility using a combination of traditional methods and the Biolog Phenotype MicroArray technique. The study found that E. latusicollum exhibited impressive metabolic versatility, being able to metabolize a majority of carbon, nitrogen, sulfur, and phosphorus sources tested, as well as adapt to different environmental conditions, including broad pH ranges and various osmolytes. The optimal medium for mycelial growth was alkyl ester agar medium, while oatmeal agar medium was optimal for sporulation, and the optimum temperature for mycelial growth was 25°C. The lethal temperature was 40°C. The study also identified arbutin and amygdalin as optimal carbon sources and Ala-Asp and Ala-Glu as optimal nitrogen sources for E. latusicollum. Furthermore, the genome of E. latusicollum strain T41 was sequenced using Illumina HiSeq and Pacific Biosciences technologies, with 10,821 genes predicted using Nonredundant, Gene Ontology, Clusters of Orthologous Groups, Kyoto Encyclopedia of Genes and Genomes, and SWISS-PROT databases. Analysis of the metabolic functions of phyllosphere microorganisms on diseased tobacco leaves affected by E. latusicollum using the Biolog Eco microplate revealed an inability to efficiently metabolize a total of 29 carbon sources, with only tween 40 showing some metabolizing ability. The study provides new insights into the structure and function of phyllosphere microbiota and highlights important challenges for future research, as well as a theoretical basis for the integrated control and breeding for disease resistance of tobacco Epicoccus leaf spot. This information can be useful in developing new strategies for disease control and management, as well as enhancing crop productivity and quality.

Profiling The Compendium Of Changes In Saccharomyces cerevisiae Due To Mutations That Alter Availability Of The Main Methyl Donor S-Adenosylmethionine

The SAM1 and SAM2 genes encode for S-AdenosylMethionine (AdoMet) synthetase enzymes, with AdoMet serving as the main methyl donor. We have previously shown that independent deletion of these genes alters chromosome stability and AdoMet concentrations in opposite ways in S. cerevisiae. To characterize other changes occurring in these mutants, we grew wildtype, sam1∆/sam1∆, and sam2∆/sam2∆ strains in 15 different Phenotypic Microarray plates with different components, equal to 1440 wells, and measured for growth variations. RNA-Sequencing was also carried out on these strains and differential gene expression determined for each mutant. In this study, we explore how the phenotypic growth differences are linked to the altered gene expression, and thereby predict the mechanisms by which loss of the SAM genes and subsequent AdoMet level changes, impact S. cerevisiae pathways and processes. We present six stories, discussing changes in sensitivity or resistance to azoles, cisplatin, oxidative stress, arginine biosynthesis perturbations, DNA synthesis inhibitors, and tamoxifen, to demonstrate the power of this novel methodology to broadly profile changes due to gene mutations. The large number of conditions that result in altered growth, as well as the large number of differentially expressed genes with wide-ranging functionality, speaks to the broad array of impacts that altering methyl donor abundance can impart, even when the conditions tested were not specifically selected as targeting known methyl involving pathways. Our findings demonstrate that some cellular changes are directly related to AdoMet-dependent methyltransferases and AdoMet availability, some are directly linked to the methyl cycle and its role is production of several important cellular components, and others reveal impacts of SAM gene mutations on previously unconnected pathways.

A computational investigation of cis-gene regulation in evolution

In biological processes involving gene networks, genes regulate other genes that determine the phenotypic traits. Gene regulation plays an important role in evolutionary dynamics. In a genetic algorithm, a trans-gene regulatory mechanism was shown to speed up adaptation and evolution. Here, we examine the effect of cis-gene regulation on an adaptive system. The model is haploid. A chromosome is partitioned into regulatory loci and structural loci. The regulatory genes regulate the expression and functioning of structural genes via the cis-elements in a probabilistic manner. In the simulation, the change in the allele frequency, the mean population fitness and the efficiency of phenotypic selection are monitored. Cis-gene regulation increases adaption and accelerates the evolutionary process in comparison with the case involving absence of gene regulation. Some special features of the simulation results are as follows. A low ratio of regulatory loci and structural loci gives higher adaptation for fixed total number of loci. Plasticity is advantageous beyond a threshold value. Adaptation is better for large number of total loci when the ratio of regulatory loci to structural loci is one. However, it reaches a saturation beyond which the increase in the total loci is not advantageous. Efficiency of the phenotypic selection is higher for larger value of the initial plasticity.

Phenotypic and Genomic Difference among Four Botryosphaeria Pathogens in Chinese Hickory Trunk Canker

Botryosphaeria species are amongst the most widespread and important canker and dieback pathogens of trees worldwide, with B. dothidea as one of the most common Botryosphaeria species. However, the information related to the widespread incidence and aggressiveness of B. dothidea among various Botryosphaeria species causing trunk cankers is still poorly investigated. In this study, the metabolic phenotypic diversity and genomic differences of four Chinese hickory canker-related Botryosphaeria pathogens, including B. dothidea, B. qingyuanensis, B. fabicerciana, and B. corticis, were systematically studied to address the competitive fitness of B. dothidea. Large-scale screening of physiologic traits using a phenotypic MicroArray/OmniLog system (PMs) found B. dothidea has a broader spectrum of nitrogen source and greater tolerance toward osmotic pressure (sodium benzoate) and alkali stress among Botryosphaeria species. Moreover, the annotation of B. dothidea species-specific genomic information via a comparative genomics analysis found 143 B. dothidea species-specific genes that not only provides crucial cues in the prediction of B. dothidea species-specific function but also give a basis for the development of a B. dothidea molecular identification method. A species-specific primer set Bd_11F/Bd_11R has been designed based on the sequence of B. dothidea species-specific gene jg11 for the accurate identification of B. dothidea in disease diagnoses. Overall, this study deepens the understanding in the widespread incidence and aggressiveness of B. dothidea among various Botryosphaeria species, providing valuable clues to assist in trunk cankers management.

Antimicrobial Activities and Mode of Flavonoid Actions

The emergence of antibiotics-resistant bacteria has been a serious concern for medical professionals over the last decade. Therefore, developing new and effective antimicrobials with modified or different modes of action is a continuing imperative. In this context, our study focuses on evaluating the antimicrobial activity of different chemically synthesized flavonoids (FLAV) to guide the chemical synthesis of effective antimicrobial molecules. A set of 12 synthesized molecules (4 chalcones, 4 flavones and 4 flavanones), bearing substitutions with chlorine and bromine groups at the C6' position and methoxy group at the C4' position of the B-ring were evaluated for antimicrobial activity toward 9 strains of Gram-positive and Gram-negative bacteria and 3 fungal strains. Our findings showed that most tested FLAV exhibited moderate to high antibacterial activity, particularly against Staphylococcus aureus with minimum inhibitory concentrations (MIC) between the range of 31.25 and 125 μg/mL and that chalcones were more efficient than flavones and flavanones. The examined compounds were also active against the tested fungi with a strong structure-activity relationship (SAR). Interestingly, leakage measurements of the absorbent material at 260 nm and scanning electron microscopy (SEM) demonstrated that the brominated chalcone induced a significant membrane permeabilization of S. aureus.

Evidence for Complex Interplay between Quorum Sensing and Antibiotic Resistance in Pseudomonas aeruginosa

Quorum sensing (QS) is a cell-density-dependent, intercellular communication system mediated by small diffusible signaling molecules. QS regulates a range of bacterial behaviors, including biofilm formation, virulence, drug resistance mechanisms, and antibiotic tolerance. Enzymes capable of degrading signaling molecules can interfere in QS-a process termed as quorum quenching (QQ). Remarkably, previous work reported some cases where enzymatic interference in QS was synergistic to antibiotics against Pseudomonas aeruginosa. The premise of combination therapy is attractive to fight against multidrug-resistant bacteria, yet comprehensive studies are lacking. Here, we evaluate the effects of QS signal disruption on the antibiotic resistance profile of P. aeruginosa by testing 222 antibiotics and antibacterial compounds from 15 different classes. We found compelling evidence that QS signal disruption does indeed affect antibiotic resistance (40% of all tested compounds; 89/222), albeit not always synergistically (not synergistic for 19% of compounds; 43/222). For some tested antibiotics, such as sulfathiazole and trimethoprim, we were able to relate the changes in resistance caused by QS signal disruption to the modulation of the expression of key genes of the folate biosynthetic pathway. Moreover, using a P. aeruginosa-based Caenorhabditis elegans killing model, we confirmed that enzymatic QQ modulates the effects of antibiotics on P. aeruginosa's pathogenicity in vivo. Altogether, these results show that signal disruption has profound and complex effects on the antibiotic resistance profile of P. aeruginosa. This work suggests that combination therapy including QQ and antibiotics should be discussed not globally but, rather, in case-by-case studies. IMPORTANCE Quorum sensing (QS) is a cell-density-dependent communication system used by a wide range of bacteria to coordinate behaviors. Strategies pertaining to the interference in QS are appealing approaches to control microbial behaviors that depend on QS, including virulence and biofilms. Interference in QS was previously reported to be synergistic with antibiotics, yet no systematic assessment exists. Here, we evaluate the potential of combination treatments using the model opportunistic human pathogen Pseudomonas aeruginosa PA14. In this model, collected data demonstrate that QS largely modulates the antibiotic resistance profile of PA14 (for more than 40% of the tested drugs). However, the outcome of combination treatments is synergistic for only 19% of them. This research demonstrates the complex relationship between QS and antibiotic resistance and suggests that combination therapy including QS inhibitors and antibiotics should be discussed not globally but, rather, in case-by-case studies.

Host and microbial-derived metabolites for Clostridioides difficile infection: Contributions, mechanisms and potential applications

Clostridioides difficile infection (CDI), which mostly occurs in hospitalized patients, is the most common and costly health care-associated disease. However, the biology of C. difficile remains incompletely understood. Current therapeutics are still challenged by the frequent recurrence of CDI. Advances in metabolomics facilitate our understanding of the etiology of CDI, which is not merely an alteration in the structure of the gut microbial community but also a dysbiosis metabolic setting promoting the germination, expansion and virulence of C. difficile. Therefore, we summarized the gut microbial and metabolic profiles for CDI under different conditions, such as those of postantibiotic treatment and postfecal microbiota transplantation. The current understanding of the role of host and gut microbial-derived metabolites as well as other nutrients in preventing or alleviating the disease symptoms of CDI will also be provided in this review. We hope that a specific nutrient-centric dietary strategy or the administration of certain nutrients to the colon could serve as an alternate line of investigation for the prophylaxis and mitigation of CDI in the future. Nevertheless, rigorously designed basic studies and randomized controlled trials need to be conducted to assess the functional mechanisms and effects of such therapeutics.

Comparing Deep Learning Approaches for Understanding Genotype × Phenotype Interactions in Biomass Sorghum

We explore the use of deep convolutional neural networks (CNNs) trained on overhead imagery of biomass sorghum to ascertain the relationship between single nucleotide polymorphisms (SNPs), or groups of related SNPs, and the phenotypes they control. We consider both CNNs trained explicitly on the classification task of predicting whether an image shows a plant with a reference or alternate version of various SNPs as well as CNNs trained to create data-driven features based on learning features so that images from the same plot are more similar than images from different plots, and then using the features this network learns for genetic marker classification. We characterize how efficient both approaches are at predicting the presence or absence of a genetic markers, and visualize what parts of the images are most important for those predictions. We find that the data-driven approaches give somewhat higher prediction performance, but have visualizations that are harder to interpret; and we give suggestions of potential future machine learning research and discuss the possibilities of using this approach to uncover unknown genotype × phenotype relationships.

Long-lasting effects of lipopolysaccharide on the reproduction and splenic transcriptome of hens and their offspring

Lipopolysaccharide (LPS) is ubiquitous in the environment and is released after the death of gram-negative bacteria, which may be related to inflammation and immunosuppression. However, its impact on the reproduction of animals and their offspring, especially the underlying mechanism need further elucidation. Here, we used laying hens as a model organism to investigate the effects of maternal exposure to LPS (LPS maternal stimulation) on animal and their offspring's immunity and reproductive performance, as well as the regulatory role of the transcriptome. We found that the LPS maternal stimulation could reduce the egg-laying rate of hens and their offspring, especially during the early and late laying stages. The transcriptome study of the spleen in F0, F1 and F2 generations showed that the maternal stimulation of the LPS affects the patterns of gene expression in laying hens, and this change has a long-lasting effect. Further analysis of DEGs and their enrichment pathways found that the LPS maternal stimulation mainly affects the reproduction and immunity of laying hens and their offspring. The DEGs such as AVD, HPS5, CATHL2, S100A12, EXFABP, RSFR, LY86, PKD4, XCL1, FOS, TREM2 and MST1 may play an essential role in the regulation of the immunity and egg-laying rate of hens. Furthermore, the MMR1L3, C3, F13A1, LY86 and GDPD2 genes with heritable effects are highly correlated with the egg-laying rate, may have an important reference value for further research. Our study reveals the profound implications of LPS exposure on immunity and reproduction of offspring, elaborating the impact of immune alteration on the egg-laying rate, emphasizing the regulatory role of intergenerational transmission of the transcriptome, implying that the environment parents being exposed to has an important impact on offspring.

The Insertion in the 3' UTR of Pmel17 Is the Causal Variant for Golden Skin Color in Tilapia

Understanding of the relationships between genotypes and phenotypes is a central problem in biology. Although teleosts have colorful phenotypes, not much is known about their underlying mechanisms. Our previous study showed that golden skin color in Mozambique tilapia was mapped in the major locus containing the Pmel gene, and an insertion in 3' UTR of Pmel17 was fully correlated with the golden color. However, the molecular mechanism of how Pmel17 determines the golden skin color is unknown. In this study, knockout of Pmel17 with CRISPR/Cas9 in blackish tilapias resulted in golden coloration, and rescue of Pmel17 in golden tilapias recovered the wild-type blackish color, indicating that Pmel17 is the gene determining the golden and blackish color. Functional analysis in vitro showed that the insertion in the 3' UTR of Pmel17 reduced the transcripts of Pmel17. Our data supplies more evidence to support that Pmel17 is the gene for blackish and golden colors, and highlights that the insertion in the 3' UTR of Pmel17 is the causative mutation for the golden coloration.

Colletotrichum Spp. Diversity Between Leaf Anthracnose and Crown Rot From the Same Strawberry Plant

Leaf anthracnose (LA) and anthracnose crown rot (ACR) represent serious fungal diseases that pose significant threats to strawberry production. To characterize the pathogen diversity associated with above diseases, 100 strawberry plants, including varieties of "Hongjia," "Zhangji," and "Tianxianzui," were sampled from Jiande and Zhoushan, the primary plantation regions of Zhejiang province, China. A total of 309 Colletotrichum isolates were isolated from crown (150 isolates) and leaves (159 isolates) of affected samples. Among these, 100 isolates obtained from the plants showing both LA and CR symptoms were selected randomly for further characterization. Based on the morphological observations combined with phylogenetic analysis of multiple genes (ACT, ITS, CAL, GAPDH, and CHS), all the 100 tested isolates were identified as C. gloeosporioides species complex, including 91 isolates of C. siamense, 8 isolates of C. fructicola causing both LA and ACR, and one isolate of C. aenigma causing ACR. The phenotypic characteristics of these isolated species were investigated using the BIOLOG phenotype MicroArray (PM) and a total of 950 different metabolic phenotype were tested, showing the characteristics among these isolates and providing the theoretical basis for pathogenic biochemistry and metabolism. The pathogenicity tests showed that even the same Colletotrichum species isolated from different diseased tissues (leaves or crowns) had significantly different pathogenicity toward strawberry leaves and crown. C. siamense isolated from diseased leaves (CSLA) was more aggressive than C. siamense isolated from rotted crown (CSCR) during the infection on "Zhangji" leaves. Additionally, C. fructicola isolated from affected leaf (CFLA) caused more severe symptoms on the leaves of four strawberry varieties compared to C. fructicola isolated from diseased crown (CFCR). For crown rot, the pathogenicity of CSCR was higher than that of CSLA.

Consequences of Mixotrophy on Cell Energetic Metabolism in Microchloropsis gaditana Revealed by Genetic Engineering and Metabolic Approaches

Algae belonging to the Microchloropsis genus are promising organisms for biotech purposes, being able to accumulate large amounts of lipid reserves. These organisms adapt to different trophic conditions, thriving in strict photoautotrophic conditions, as well as in the concomitant presence of light plus reduced external carbon as energy sources (mixotrophy). In this work, we investigated the mixotrophic responses of Microchloropsis gaditana (formerly Nannochloropsis gaditana). Using the Biolog growth test, in which cells are loaded into multiwell plates coated with different organic compounds, we could not find a suitable substrate for Microchloropsis mixotrophy. By contrast, addition of the Lysogeny broth (LB) to the inorganic growth medium had a benefit on growth, enhancing respiratory activity at the expense of photosynthetic performances. To further dissect the role of respiration in Microchloropsis mixotrophy, we focused on the mitochondrial alternative oxidase (AOX), a protein involved in energy management in other algae prospering in mixotrophy. Knocking-out the AOX1 gene by transcription activator-like effector nuclease (TALE-N) led to the loss of capacity to implement growth upon addition of LB supporting the hypothesis that the effect of this medium was related to a provision of reduced carbon. We conclude that mixotrophic growth in Microchloropsis is dominated by respiratory rather than by photosynthetic energetic metabolism and discuss the possible reasons for this behavior in relationship with fatty acid breakdown via β-oxidation in this oleaginous alga.

Characterization of Cold-Tolerant Saccharomyces cerevisiae Cheongdo Using Phenotype Microarray

The cold-tolerant yeast Saccharomyces cerevisiae is industrially useful for lager fermentation, high-quality wine, and frozen dough production. S. cerevisiae Cheongdo is a recent isolate from frozen peach samples which has a good fermentation performance at low temperatures and desirable flavor profiles. Here, phenotype microarray was used to investigate industrial potentials of S. cerevisiae Cheongdo using 192 carbon sources. Compared to commercial wine yeast S. cerevisiae EC1118, Cheongdo showed significantly different growth rates on 34 substrates. The principal component analysis of the results highlighted that the better growth of Cheongdo on galactose than on EC1118 was the most significant difference between the two strains. The intact GAL4 gene and the galactose fermentation performance at a low temperatures suggested that S. cerevisiae Cheongdo is a promising host for industrial fermentation rich in galactose, such as lactose and agarose.

Deep Learning for Reintegrating Biology

The goal of this vision paper is to investigate the possible role that advanced machine learning techniques, especially deep learning, could play in the reintegration of various biological disciplines. To achieve this goal, a series of operational, but admittedly very simplistic, conceptualizations have been introduced: Life has been taken as a multidimensional phenomenon that inhabits three physical dimensions (time, space, and scale) and biological research as establishing connection between different points in the domain of life. Each of these points hence denotes a position in time, space, and scale at which a life phenomenon of interest takes place. Using these conceptualizations, fragmentation of biology can be seen as the result of too few and especially too short-ranged connections. Reintegrating biology could then be accomplished by establishing more, longer ranged connections. Deep learning methods appear to be very well suited for addressing this particular need at this particular time. Not withstanding the numerous unsubstantiated claims regarding the capabilities of AI, deep learning networks represent a major advance in the ability to find complex relationships inside large data sets that would have not been accessible with traditional data analytic methods or to a human observer. In addition, ongoing advances in the automation of taking measurements from phenomena on all levels of biological organization, continue to increase the number of large quantitative data sets that are available. These increasingly common data sets could serve as anchor points for making long-range connections by virtue of deep learning. However, connections within the domain of life are likely to be structured in a highly nonuniform fashion and hence it is necessary to develop methods, e.g., theoretical, computational, and experimental, to determine linkage of biological data sets most likely to provide useful insights on a biological problem using deep learning. Finally, specific deep learning approaches and architectures should be developed to match the needs of reintegrating biology.

Population structure and uropathogenic potential of extended-spectrum cephalosporin-resistant Escherichia coli from retail chicken meat

Background

Food-producing animals and their products are considered a source for human acquisition of antimicrobial resistant (AMR) bacteria, and poultry are suggested to be a reservoir for Escherichia coli resistant to extended-spectrum cephalosporins (ESC), a group of antimicrobials used to treat community-onset urinary tract infections in humans. However, the zoonotic potential of ESC-resistant E. coli from poultry and their role as extraintestinal pathogens, including uropathogens, have been debated. The aim of this study was to characterize ESC-resistant E. coli isolated from domestically produced retail chicken meat regarding their population genetic structure, the presence of virulence-associated geno- and phenotypes as well as their carriage of antimicrobial resistance genes, in order to evaluate their uropathogenic potential.

Results

A collection of 141 ESC-resistant E. coli isolates from retail chicken in the Norwegian monitoring program for antimicrobial resistance in bacteria from food, feed and animals (NORM-VET) in 2012, 2014 and 2016 (n = 141) were whole genome sequenced and analyzed. The 141 isolates, all containing the beta-lactamase encoding gene bla_CMY-2, were genetically diverse, grouping into 19 different sequence types (STs), and temporal variations in the distribution of STs were observed. Generally, a limited number of virulence-associated genes were identified in the isolates. Eighteen isolates were selected for further analysis of uropathogen-associated virulence traits including expression of type 1 fimbriae, motility, ability to form biofilm, serum resistance, adhesion- and invasion of eukaryotic cells and colicin production. These isolates demonstrated a high diversity in virulence-associated phenotypes suggesting that the uropathogenicity of ESC-resistant E. coli from chicken meat is correspondingly highly variable. For some isolates, there was a discrepancy between the presence of virulence-associated genes and corresponding expected phenotype, suggesting that mutations or regulatory mechanisms could influence their pathogenic potential.

Conclusion

Our results indicate that the ESC-resistant E. coli from chicken meat have a low uropathogenic potential to humans, which is important knowledge for improvement of future risk assessments of AMR in the food chains.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02160-y.

A consensus S. cerevisiae metabolic model Yeast8 and its ecosystem for comprehensively probing cellular metabolism

Genome-scale metabolic models (GEMs) represent extensive knowledgebases that provide a platform for model simulations and integrative analysis of omics data. This study introduces Yeast8 and an associated ecosystem of models that represent a comprehensive computational resource for performing simulations of the metabolism of Saccharomyces cerevisiae--an important model organism and widely used cell-factory. Yeast8 tracks community development with version control, setting a standard for how GEMs can be continuously updated in a simple and reproducible way. We use Yeast8 to develop the derived models panYeast8 and coreYeast8, which in turn enable the reconstruction of GEMs for 1,011 different yeast strains. Through integration with enzyme constraints (ecYeast8) and protein 3D structures (proYeast8DB), Yeast8 further facilitates the exploration of yeast metabolism at a multi-scale level, enabling prediction of how single nucleotide variations translate to phenotypic traits.

Characterization of the Widely Distributed Novel ECF42 Group of Extracytoplasmic Function σ Factors in Streptomyces venezuelae

Extracytoplasmic function σ factors (ECFs) represent the third most abundant fundamental principle of bacterial signal transduction, outranked only by one- and two-component systems. A recent census of ECFs revealed a large number of novel groups whose functions and regulatory mechanisms have not yet been elucidated. Here, we report the characterization of members of the novel group ECF42. ECF42 is a highly abundant and widely distributed ECF group that is present in 11 phyla but is predominantly found in Actinobacteria Analysis of the genomic context conservation did not identify a putative anti-σ factor. Instead, ECF42 genes are cotranscribed with genes encoding a conserved DGPF protein. We have experimentally verified the target promoter of these ECFs (TGTCGA in the -35 region and CGA/TC in the -10 region), which was found upstream of the ECF42-encoding operons in Streptomyces venezuelae, suggesting that ECF42s are positively autoregulated. RNA sequencing (RNA-seq) was performed to define the regulons of the three ECF42 proteins in S. venezuelae, which identified mostly genes encoding DGPF proteins. In contrast to typical ECFs, ECF42 proteins harbor a long C-terminal extension, which is crucial for their activity. Our work provides the first analysis of the function and regulatory mechanism of this novel ECF group that contains a regulatory C-terminal extension.IMPORTANCE In contrast to the one- and two-component signal transduction systems in bacteria, the importance and diversity of ECFs have only recently been recognized in the course of comprehensive phylogenetic and comparative genomics studies. Thus, most of the ECFs still have not been experimentally characterized regarding their physiological functions and regulation mechanisms so far. The physiological roles, target promoter, and target regulons of a novel group of ECFs, ECF42, in S. venezuelae have been investigated in this work. More importantly, members of this group are characterized by a C-terminal extension, which has been verified to harbor a regulatory role in ECF42s. Hence, our work provides an important source for further research on such C-terminal extension containing ECFs.

Isolation, Development, and Genomic Analysis of Bacillus megaterium SR7 for Growth and Metabolite Production Under Supercritical Carbon Dioxide

Supercritical carbon dioxide (scCO2) is an attractive substitute for conventional organic solvents due to its unique transport and thermodynamic properties, its renewability and labile nature, and its high solubility for compounds such as alcohols, ketones, and aldehydes. However, biological systems that use scCO2 are mainly limited to in vitro processes due to its strong inhibition of cell viability and growth. To solve this problem, we used a bioprospecting approach to isolate a microbial strain with the natural ability to grow while exposed to scCO2. Enrichment culture and serial passaging of deep subsurface fluids from the McElmo Dome scCO2 reservoir in aqueous media under scCO2 headspace enabled the isolation of spore-forming strain Bacillus megaterium SR7. Sequencing and analysis of the complete 5.51 Mbp genome and physiological characterization revealed the capacity for facultative anaerobic metabolism, including fermentative growth on a diverse range of organic substrates. Supplementation of growth medium with L-alanine for chemical induction of spore germination significantly improved growth frequencies and biomass accumulation under scCO2 headspace. Detection of endogenous fermentative compounds in cultures grown under scCO2 represents the first observation of bioproduct generation and accumulation under this condition. Culturing development and metabolic characterization of B. megaterium SR7 represent initial advancements in the effort toward enabling exploitation of scCO2 as a sustainable solvent for in vivo bioprocessing.

Investigating mixotrophic metabolism in the model diatom Phaeodactylum tricornutum

Diatoms are prominent marine microalgae, interesting not only from an ecological point of view, but also for their possible use in biotechnology applications. They can be cultivated in phototrophic conditions, using sunlight as the sole energy source. Some diatoms, however, can also grow in a mixotrophic mode, wherein both light and external reduced carbon contribute to biomass accumulation. In this study, we investigated the consequences of mixotrophy on the growth and metabolism of the pennate diatom Phaeodactylum tricornutum, using glycerol as the source of reduced carbon. Transcriptomics, metabolomics, metabolic modelling and physiological data combine to indicate that glycerol affects the central-carbon, carbon-storage and lipid metabolism of the diatom. In particular, provision of glycerol mimics typical responses of nitrogen limitation on lipid metabolism at the level of triacylglycerol accumulation and fatty acid composition. The presence of glycerol, despite provoking features reminiscent of nutrient limitation, neither diminishes photosynthetic activity nor cell growth, revealing essential aspects of the metabolic flexibility of these microalgae and suggesting possible biotechnological applications of mixotrophy.This article is part of the themed issue 'The peculiar carbon metabolism in diatoms'.

Metabolic Phenotype Characterization of Botrytis cinerea, the Causal Agent of Gray Mold

Botrytis cinerea, which causes gray mold, is an important pathogen in four important economic crops, tomato, tobacco, cucumber and strawberry, in China and worldwide. Metabolic phenomics data on B. cinerea isolates from these four crops were characterized and compared for 950 phenotypes with a BIOLOG Phenotype MicroArray (PM). The results showed that the metabolic fingerprints of the four B. cinerea isolates were similar to each other with minimal differences. B. cinerea isolates all metabolized more than 17% of the tested carbon sources, 63% of the amino acid nitrogen substrates, 80% of the peptide nitrogen substrates, 93% of the phosphorus substrates, and 97% of the sulfur substrates. Carbon substrates of organic acids and carbohydrates, and nitrogen substrates of amino acids and peptides were the significant utilization patterns for B. cinerea. Each B. cinerea isolate contained 94 biosynthetic pathways. These isolates showed a large range of adaptabilities and were still able to metabolize substrates in the presence of the osmolytes, including up to 6% potassium chloride, 10% sodium chloride, 5% sodium sulfate, 6% sodium formate, 20% ethylene glycol, and 3% urea. These isolates all showed active metabolism in environments with pH values from 3.5 to 8.5 and exhibited decarboxylase activities. These characterizations provide a theoretical basis for the study of B. cinerea in biochemistry and metabolic phenomics and provide valuable clues to finding potential new ways to manage gray mold.

Altered Distribution of RNA Polymerase Lacking the Omega Subunit within the Prophages along the Escherichia coli K-12 Genome

The RNA polymerase (RNAP) of Escherichia coli K-12 is a complex enzyme consisting of the core enzyme with the subunit structure α2ββ'ω and one of the σ subunits with promoter recognition properties. The smallest subunit, omega (the rpoZ gene product), participates in subunit assembly by supporting the folding of the largest subunit, β', but its functional role remains unsolved except for its involvement in ppGpp binding and stringent response. As an initial approach for elucidation of its functional role, we performed in this study ChIP-chip (chromatin immunoprecipitation with microarray technology) analysis of wild-type and rpoZ-defective mutant strains. The altered distribution of RpoZ-defective RNAP was identified mostly within open reading frames, in particular, of the genes inside prophages. For the genes that exhibited increased or decreased distribution of RpoZ-defective RNAP, the level of transcripts increased or decreased, respectively, as detected by reverse transcription-quantitative PCR (qRT-PCR). In parallel, we analyzed, using genomic SELEX (systemic evolution of ligands by exponential enrichment), the distribution of constitutive promoters that are recognized by RNAP RpoD holoenzyme alone and of general silencer H-NS within prophages. Since all 10 prophages in E. coli K-12 carry only a small number of promoters, the altered occupancy of RpoZ-defective RNAP and of transcripts might represent transcription initiated from as-yet-unidentified host promoters. The genes that exhibited transcription enhanced by RpoZ-defective RNAP are located in the regions of low-level H-NS binding. By using phenotype microarray (PM) assay, alterations of some phenotypes were detected for the rpoZ-deleted mutant, indicating the involvement of RpoZ in regulation of some genes. Possible mechanisms of altered distribution of RNAP inside prophages are discussed. IMPORTANCE The 91-amino-acid-residue small-subunit omega (the rpoZ gene product) of Escherichia coli RNA polymerase plays a structural role in the formation of RNA polymerase (RNAP) as a chaperone in folding the largest subunit (β', of 1,407 residues in length), but except for binding of the stringent signal ppGpp, little is known of its role in the control of RNAP function. After analysis of genomewide distribution of wild-type and RpoZ-defective RNAP by the ChIP-chip method, we found alteration of the RpoZ-defective RNAP inside open reading frames, in particular, of the genes within prophages. For a set of the genes that exhibited altered occupancy of the RpoZ-defective RNAP, transcription was found to be altered as observed by qRT-PCR assay. All the observations here described indicate the involvement of RpoZ in recognition of some of the prophage genes. This study advances understanding of not only the regulatory role of omega subunit in the functions of RNAP but also the regulatory interplay between prophages and the host E. coli for adjustment of cellular physiology to a variety of environments in nature.

Developing genome-reduced Pseudomonas chlororaphis strains for the production of secondary metabolites

BACKGROUND

The current chassis organisms or various types of cell factories have considerable advantages and disadvantages. Therefore, it is necessary to develop various chassis for an efficient production of different bioproducts from renewable resources. In this context, synthetic biology offers unique potentialities to produce value-added products of interests. Microbial genome reduction and modification are important strategies for constructing cellular chassis and cell factories. Many genome-reduced strains from Escherichia coli, Bacillus subtilis, Corynebacterium glutamicum and Streptomyces, have been widely used for the production of amino acids, organic acids, and some enzymes. Some Pseudomonas strains could serve as good candidates for ideal chassis cells since they grow fast and can produce many valuable metabolites with low nutritional requirements and strong environmental adaptability. Pseudomonas chlororaphis GP72 is a non-pathogenic plant growth-promoting rhizobacterium that possesses capacities of tolerating various environmental stresses and synthesizing many kinds of bioactive compounds with high yield. These include phenazine-1-carboxylic acid (PCA) and 2-hydroxyphenazine (2-OH-PHZ), which exhibit strong bacteriostatic and antifungal activity toward some microbial pathogens.

RESULTS

We depleted 685 kb (10.3% of the genomic sequence) from the chromosome of P. chlororaphis GP72(rpeA-) by a markerless deletion method, which included five secondary metabolic gene clusters and 17 strain-specific regions (525 non-essential genes). Then we characterized the 22 multiple-deletion series (MDS) strains. Growth characteristics, production of phenazines and morphologies were changed greatly in mutants with large-fragment deletions. Some of the genome-reduced P. chlororaphis mutants exhibited more productivity than the parental strain GP72(rpeA-). For example, strain MDS22 had 4.4 times higher production of 2-OH-PHZ (99.1 mg/L) than strain GP72(rpeA-), and the specific 2-OH-PHZ production rate (mmol/g/h) increased 11.5-fold. Also and MDS10 had the highest phenazine production (852.0 mg/L) among all the studied strains with a relatively high specific total phenazine production rate (0.0056 g/g/h).

CONCLUSIONS

In conclusion, P. chlororaphis strains with reduced genome performed better in production of secondary metabolites than the parent strain. The newly developed mutants can be used for the further genetic manipulation to construct chassis cells with the less complex metabolic network, better regulation and more efficient productivity for diverse biotechnological applications.

An Endohyphal Bacterium (Chitinophaga, Bacteroidetes) Alters Carbon Source Use by Fusarium keratoplasticum (F. solani Species Complex, Nectriaceae)

Bacterial endosymbionts occur in diverse fungi, including members of many lineages of Ascomycota that inhabit living plants. These endosymbiotic bacteria (endohyphal bacteria, EHB) often can be removed from living fungi by antibiotic treatment, providing an opportunity to assess their effects on functional traits of their fungal hosts. We examined the effects of an endohyphal bacterium (Chitinophaga sp., Bacteroidetes) on substrate use by its host, a seed-associated strain of the fungus Fusarium keratoplasticum, by comparing growth between naturally infected and cured fungal strains across 95 carbon sources with a Biolog® phenotypic microarray. Across the majority of substrates (62%), the strain harboring the bacterium significantly outperformed the cured strain as measured by respiration and hyphal density. These substrates included many that are important for plant- and seed-fungus interactions, such as D-trehalose, myo-inositol, and sucrose, highlighting the potential influence of EHB on the breadth and efficiency of substrate use by an important Fusarium species. Cases in which the cured strain outperformed the strain harboring the bacterium were observed in only 5% of substrates. We propose that additive or synergistic substrate use by the fungus-bacterium pair enhances fungal growth in this association. More generally, alteration of the breadth or efficiency of substrate use by dispensable EHB may change fungal niches in short timeframes, potentially shaping fungal ecology and the outcomes of fungal-host interactions.

The application of phenotypic microarray analysis to anti-fungal drug development

Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance.

Metabolic phenotype of clinical and environmental Mycobacterium avium subsp. hominissuis isolates

Background

Mycobacterium avium subsp. hominissuis (MAH) is an emerging opportunistic human pathogen. It can cause pulmonary infections, lymphadenitis and disseminated infections in immuno-compromised patients. In addition, MAH is widespread in the environment, since it has been isolated from water, soil or dust. In recent years, knowledge on MAH at the molecular level has increased substantially. In contrast, knowledge of the MAH metabolic phenotypes remains limited.

Methods

In this study, for the first time we analyzed the metabolic substrate utilization of ten MAH isolates, five from a clinical source and five from an environmental source. We used BIOLOG Phenotype Microarray^TM technology for the analysis. This technology permits the rapid and global analysis of metabolic phenotypes.

Results

The ten MAH isolates tested showed different metabolic patterns pointing to high intra-species diversity. Our MAH isolates preferred to use fatty acids such as Tween, caproic, butyric and propionic acid as a carbon source, and L-cysteine as a nitrogen source. Environmental MAH isolates resulted in being more metabolically active than clinical isolates, since the former metabolized more strongly butyric acid (p = 0.0209) and propionic acid (p = 0.00307).

Discussion

Our study provides new insight into the metabolism of MAH. Understanding how bacteria utilize substrates during infection might help the developing of strategies to fight such infections.

The White-Knight Hypothesis, or Does the Environment Limit Innovations?

Organisms often harbor latent traits that are byproducts of other adaptations. Such latent traits are not themselves adaptive but can become adaptive in the right environment. Here I discuss several examples of such traits. Their abundance suggests that environmental change rather than new mutations might often limit the origin of evolutionary adaptations and innovations. This is important, because environments can change much faster than new mutations arise. I introduce a conceptual model that distinguishes between mutation-limited and environment-limited trait origins and suggest how experiments could help discriminate between them. Wherever latent traits are plentiful, ecology rather than genetics might determine how fast new adaptations originate and thus how fast adaptive Darwinian evolution proceeds.

Identifying Multiple Potential Metabolic Cycles in Time-Series from Biolog Experiments

Biolog Phenotype Microarray (PM) is a technology allowing simultaneous screening of the metabolic behaviour of bacteria under a large number of different conditions. Bacteria may often undergo several cycles of metabolic activity during a Biolog experiment. We introduce a novel algorithm to identify these metabolic cycles in PM experimental data, thus increasing the potential of PM technology in microbiology. Our method is based on a statistical decomposition of the time-series measurements into a set of growth models. We show that the method is robust to measurement noise and captures accurately the biologically relevant signals from the data. Our implementation is made freely available as a part of an R package for PM data analysis and can be found at www.helsinki.fi/bsg/software/Biolog_Decomposition.

Identifying and Tackling Emergent Vulnerability in Drug-Resistant Mycobacteria

The global mechanisms and associated molecular alterations that occur in drug-resistant mycobacteria are poorly understood. To address this, we obtain genomics data and then construct a genome-scale response network in isoniazid-resistant Mycobacterium smegmatis and apply a network-mining algorithm. Through this, we decipher global alterations in an unbiased manner and identify emergent vulnerabilities in resistant bacilli, of which redox response was prominent. Using phenotypic profiling, we find that resistant bacilli exhibit collateral sensitivity to several compounds that block antioxidant responses. We find that nanogram/milliliter concentrations of ebselen, vancomycin, and phenylarsine oxide, in combination with isoniazid, are highly effective against Mycobacterium tuberculosis H37Rv and three clinical drug-resistant strains. Dynamic measurements of cytoplasmic redox potential revealed a surprisingly diminished capacity of clinical drug-resistant strains to counteract oxidative stress, providing a mechanistic basis for efficient and synergistic mycobactericidal activity of the drug combinations. Ebselen and vancomycin appear to be promising repurposable drugs.

The evolution of opsins and color vision: connecting genotype to a complex phenotype

Entender la base genética de los rasgos adaptativos es un paso crítico en el estudio de los procesos evolutivos. Para estudiar la conexión entre genotipo y fenotipo es importante definir el fenotipo a diferentes niveles: desde las proteínas que se construyen con base en un gen, hasta las características finales presentes en un organismo. Las opsinas y los fotopigmentos son elementos primordiales de la visión y entender cómo han evolucionado es fundamental en el estudio de la visión en los animales como un caracter derivado de selección natural o sexual. Este artículo se enfoca en este sistema, en el que se pueden conectar genotipo y fenotipo, como ejemplo de fenotipo complejo para ilustrar las dificultades de establecer una relación clara entre genotipo y fenotipo. Adicionalmente, este artículo tiene como objetivo discutir el funcionamiento del sistema de fotorrecepción, con énfasis particular en las aves, con el fin de enumerar varios factores que deben ser tenidos en cuenta para predecir cambios en la visión a partir del estudio de los fotopigmentos. Dado que los modelos basados en la visión de aves son cada vez más usados en diversas áreas de la biología evolutiva tales como: selección de pareja, depredación y camuflaje; se hace relevante entender los fundamentos y limitaciones de estos modelos. Por esta razón, en este artículo discuto los detalles y aspectos prácticos del uso de los modelos de visión existentes para aves, con el fin de facilitar su uso en futuras investigaciones en diversas áreas de evolución.

Whole genomic sequence analysis of Bacillus infantis: defining the genetic blueprint of strain NRRL B-14911, an emerging cardiopathogenic microbe

Background

We recently reported the identification of Bacillus sp. NRRL B-14911 that induces heart autoimmunity by generating cardiac-reactive T cells through molecular mimicry. This marine bacterium was originally isolated from the Gulf of Mexico, but no associations with human diseases were reported. Therefore, to characterize its biological and medical significance, we sought to determine and analyze the complete genome sequence of Bacillus sp. NRRL B-14911.

Results

Based on the phylogenetic analysis of 16S ribosomal RNA (rRNA) genes, sequence analysis of the 16S-23S rDNA intergenic transcribed spacers, phenotypic microarray, and matrix-assisted laser desorption ionization time-of-flight mass spectrometry, we propose that this organism belongs to the species Bacillus infantis, previously shown to be associated with sepsis in a newborn child. Analysis of the complete genome of Bacillus sp. NRRL B-14911 revealed several virulence factors including adhesins, invasins, colonization factors, siderophores and transporters. Likewise, the bacterial genome encodes a wide range of methyl transferases, transporters, enzymatic and biochemical pathways, and insertion sequence elements that are distinct from other closely related bacilli.

Conclusions

The complete genome sequence of Bacillus sp. NRRL B-14911 provided in this study may facilitate genetic manipulations to assess gene functions associated with bacterial survival and virulence. Additionally, this bacterium may serve as a useful tool to establish a disease model that permits systematic analysis of autoimmune events in various susceptible rodent strains.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2900-2) contains supplementary material, which is available to authorized users.

High-Content Screening with siRNA Optimizes a Cell Biological Approach to Drug Discovery: Defining the Role of P53 Activation in the Cellular Response to Anticancer Drugs

Deciphering the effects of compounds on molecular events within living cells is becoming an increasingly important component of drug discovery. In a model application of the industrial drug discovery process, the authors profiled a panel of 22 compounds using hierarchical cluster analysis of multiparameter high-content screening measurements from nearly 500,000 cells per microplate. RNAi protein knockdown methodology was used with high-content screening to dissect the effects of 2 anticancer drugs on multiple target activities. Camptothecin activated p53 in A549 lung carcinoma cells pretreated with scrambled siRNA, exhibited concentration-dependent cell cycle blocks, and induced moderate microtubule stabilization. Knockdown of camptothecin-induced p53 protein expression with p53 siRNA inhibited the G1/S blocking activity of the drug and diminished its microtubule-stabilizing activity. Paclitaxel activated p53 protein at low concentrations but exhibited G2/M cell cycle blocking activity at higher concentrations where microtubules were stabilized. In cells treated with p53 siRNA, paclitaxel failed to activate p53 protein, but the knockdown did not have a significant effect on the ability of paclitaxel to stabilize microtubules or induce a G2/M cell cycle block. Thus, this model application of the use of RNAi technology within the context of high-content screening shows the potential to provide massive amounts of combinatorial cell biological information on the temporal and spatial responses that cells mount to treatment by promising therapeutic candidates.

PRECOG: a tool for automated extraction and visualization of fitness components in microbial growth phenomics

BACKGROUND

Phenomics is a field in functional genomics that records variation in organismal phenotypes in the genetic, epigenetic or environmental context at a massive scale. For microbes, the key phenotype is the growth in population size because it contains information that is directly linked to fitness. Due to technical innovations and extensive automation our capacity to record complex and dynamic microbial growth data is rapidly outpacing our capacity to dissect and visualize this data and extract the fitness components it contains, hampering progress in all fields of microbiology.

RESULTS

To automate visualization, analysis and exploration of complex and highly resolved microbial growth data as well as standardized extraction of the fitness components it contains, we developed the software PRECOG (PREsentation and Characterization Of Growth-data). PRECOG allows the user to quality control, interact with and evaluate microbial growth data with ease, speed and accuracy, also in cases of non-standard growth dynamics. Quality indices filter high- from low-quality growth experiments, reducing false positives. The pre-processing filters in PRECOG are computationally inexpensive and yet functionally comparable to more complex neural network procedures. We provide examples where data calibration, project design and feature extraction methodologies have a clear impact on the estimated growth traits, emphasising the need for proper standardization in data analysis.

CONCLUSIONS

PRECOG is a tool that streamlines growth data pre-processing, phenotypic trait extraction, visualization, distribution and the creation of vast and informative phenomics databases.

Phenotype MicroArray™ system in the study of fungal functional diversity and catabolic versatility

Fungi cover a range of important ecological functions associated with nutrient and carbon cycling in leaf litter and soil. As a result, research on existing relationships between fungal functional diversity, decomposition rates and competition is of key interest. Indeed, availability of nutrients in soil is largely the consequence of organic matter degradation dynamics. The Biolog^® Phenotype MicroArrays™ (PM) system allows for the testing of fungi against many different carbon sources at any one time. The use and potential of the PM system as a tool for studying niche overlap and catabolic versatility of saprotrophic fungi is discussed here, and examples of its application are provided.

Sparse regression models for unraveling group and individual associations in eQTL mapping

Background

As a promising tool for dissecting the genetic basis of common diseases, expression quantitative trait loci (eQTL) study has attracted increasing research interest. Traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to biological pathways.

Results

To alleviate this limitation, in this paper, we propose geQTL, a sparse regression method that can detect both group-wise and individual associations between SNPs and expression traits. geQTL can also correct the effects of potential confounders. Our method employs computationally efficient technique, thus it is able to fulfill large scale studies. Moreover, our method can automatically infer the proper number of group-wise associations. We perform extensive experiments on both simulated datasets and yeast datasets to demonstrate the effectiveness and efficiency of the proposed method. The results show that geQTL can effectively detect both individual and group-wise signals and outperforms the state-of-the-arts by a large margin.

Conclusions

This paper well illustrates that decoupling individual and group-wise associations for association mapping is able to improve eQTL mapping accuracy, and inferring individual and group-wise associations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0986-9) contains supplementary material, which is available to authorized users.

Comparison of Chemical Sensitivity of Fresh and Long-Stored Heat Resistant Neosartorya fischeri Environmental Isolates Using BIOLOG Phenotype MicroArray System

Spoilage of heat processed food and beverage by heat resistant fungi (HRF) is a major problem for food industry in many countries. Neosartorya fischeri is the leading source of spoilage in thermally processed products. Its resistance to heat processing and toxigenicity makes studies about Neosartorya fischeri metabolism and chemical sensitivity essential. In this study chemical sensitivity of two environmental Neosartorya fischeri isolates were compared. One was isolated from canned apples in 1923 (DSM3700), the other from thermal processed strawberry product in 2012 (KC179765), used as long-stored and fresh isolate, respectively. The study was conducted using Biolog Phenotype MicroArray platforms of chemical sensitivity panel and traditional hole-plate method. The study allowed for obtaining data about Neosartorya fischeri growth inhibitors. The fresh isolate appeared to be much more resistant to chemical agents than the long-stored isolate. Based on phenotype microarray assay nitrogen compounds, toxic cations and membrane function compounds were the most effective in growth inhibition of N. fischeri isolates. According to the study zaragozic acid A, thallium(I) acetate and sodium selenate were potent and promising N. fischeri oriented fungicides which was confirmed by both chemical sensitivity microplates panel and traditional hole-plate methods.