Spatial scale affects landscape genetic analysis of a wetland grasshopper

Most landscape genetic studies assess the impact of landscape elements on species' dispersal and gene flow. Many of these studies perform their analysis on all possible population pairs in a study area and do not explicitly consider the effects of spatial scale and population network topology on their results. Here, we examined the effects of spatial scale and population network topology on the outcome of a landscape genetic analysis. Additionally, we tested whether the relevant spatial scale of landscape genetic analysis could be defined by population network topology or by isolation‐by‐distance (IBD) patterns. A data set of the wetland grasshopper Stethophyma grossum, collected in a fragmented agricultural landscape, was used to analyse population network topology, IBD patterns and dispersal habitats, using least‐cost transect analysis. Landscape genetic analyses neglecting spatial scale and population network topology resulted in models with low fits, with which a most likely dispersal habitat could not be identified. In contrast, analyses considering spatial scale and population network topology resulted in high model fits by restricting landscape genetic analysis to smaller scales (0–3 km) and neighbouring populations, as represented by a Gabriel graph. These models also successfully identified a likely dispersal habitat of S. grossum. The above results suggest that spatial scale and potentially population network topology should be more explicitly considered in future landscape genetic analyses.     

The catalytic domain of the germination-specific lytic transglycosylase SleB from Bacillus anthracis displays a unique active site topology

Bacillus anthracis produces metabolically inactive spores. Germination of these spores requires germination‐specific lytic enzymes (GSLEs) that degrade the unique cortex peptidoglycan to permit resumption of metabolic activity and outgrowth. We report the first crystal structure of the catalytic domain of a GSLE, SleB. The structure revealed a transglycosylase fold with unique active site topology and permitted identification of the catalytic glutamate residue. Moreover, the structure provided insights into the molecular basis for the specificity of the enzyme for muramic‐δ‐lactam‐containing cortex peptidoglycan. The protein also contains a metal‐binding site that is positioned directly at the entrance of the substrate‐binding cleft. Proteins 2012;. © 2012 Wiley Periodicals, Inc.     

Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach

Background

Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network.

Methodology/Principal Findings

Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response.

Conclusions/Significance

Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.     

Exploiting cell‐free systems: Implementation and debugging of a system of biotransformations

The orchestration of a multitude of enzyme catalysts allows cells to carry out complex and thermodynamically unfavorable chemical conversions. In an effort to recruit these advantages for in vitro biotransformations, we have assembled a 10‐step catalytic system—a system of biotransformations (SBT)—for the synthesis of unnatural monosaccharides based on the versatile building block dihydroxyacetone phosphate (DHAP). To facilitate the assembly of such a network, we have insulated a production pathway from Escherichia coli's central carbon metabolism. This pathway consists of the endogenous glycolysis without triose‐phosphate isomerase to enable accumulation of DHAP and was completed with lactate dehydrogenase to regenerate NAD⁺. It could be readily extended for the synthesis of unnatural sugar molecules, such as the unnatural monosaccharide phosphate 5,6,7‐trideoxy‐D ‐threo‐heptulose‐1‐phosphate from DHAP and butanal. Insulation required in particular inactivation of the amn gene encoding the AMP nucleosidase, which otherwise led to glucose‐independent DHAP production from adenosine phosphates. The work demonstrates that a sufficiently insulated in vitro multi‐step enzymatic system can be readily assembled from central carbon metabolism pathways. Biotechnol. Bioeng. 2010; 106: 376–389. © 2010 Wiley Periodicals, Inc.     

The unusual di‐domain structure of Dunaliella salina glycerol‐3‐phosphate dehydrogenase enables direct conversion of dihydroxyacetone phosphate to glycerol

Dunaliella has been extensively studied due to its intriguing adaptation to high salinity. Its di‐domain glycerol‐3‐phosphate dehydrogenase (GPDH) isoform is likely to underlie the rapid production of the osmoprotectant glycerol. Here, we report the structure of the chimeric Dunaliella salina GPDH (DsGPDH) protein featuring a phosphoserine phosphatase‐like domain fused to the canonical glycerol‐3‐phosphate (G3P) dehydrogenase domain. Biochemical assays confirm that DsGPDH can convert dihydroxyacetone phosphate (DHAP) directly to glycerol, whereas a separate phosphatase protein is required for this conversion process in most organisms. The structure of DsGPDH in complex with its substrate DHAP and co‐factor nicotinamide adenine dinucleotide (NAD) allows the identification of the residues that form the active sites. Furthermore, the structure reveals an intriguing homotetramer form that likely contributes to the rapid biosynthesis of glycerol.     

A comprehensive genome‐scale reconstruction of Escherichia coli metabolism—2011

The initial genome‐scale reconstruction of the metabolic network of Escherichia coli K‐12 MG1655 was assembled in 2000. It has been updated and periodically released since then based on new and curated genomic and biochemical knowledge. An update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. iJO1366 was (1) updated in part using a new experimental screen of 1075 gene knockout strains, illuminating cases where alternative pathways and isozymes are yet to be discovered, (2) compared with its predecessor and to experimental data sets to confirm that it continues to make accurate phenotypic predictions of growth on different substrates and for gene knockout strains, and (3) mapped to the genomes of all available sequenced E. coli strains, including pathogens, leading to the identification of hundreds of unannotated genes in these organisms. Like its predecessors, the iJO1366 reconstruction is expected to be widely deployed for studying the systems biology of E. coli and for metabolic engineering applications.     

Stirred tank bioreactor culture combined with serum‐/xenogeneic‐free culture medium enables an efficient expansion of umbilical cord‐derived mesenchymal stem/stromal cells

Mesenchymal stem/stromal cells (MSC) are being widely explored as promising candidates for cell‐based therapies. Among the different human MSC origins exploited, umbilical cord represents an attractive and readily available source of MSC that involves a non‐invasive collection procedure. In order to achieve relevant cell numbers of human MSC for clinical applications, it is crucial to develop scalable culture systems that allow bioprocess control and monitoring, combined with the use of serum/xenogeneic (xeno)‐free culture media. In the present study, we firstly established a spinner flask culture system combining gelatin‐based Cultispher^®S microcarriers and xeno‐free culture medium for the expansion of umbilical cord matrix (UCM)‐derived MSC. This system enabled the production of 2.4 (±1.1) x10⁵ cells/mL (n = 4) after 5 days of culture, corresponding to a 5.3 (±1.6)‐fold increase in cell number. The established protocol was then implemented in a stirred‐tank bioreactor (800 mL working volume) (n = 3) yielding 115 million cells after 4 days. Upon expansion under stirred conditions, cells retained their differentiation ability and immunomodulatory potential. The development of a scalable microcarrier‐based stirred culture system, using xeno‐free culture medium that suits the intrinsic features of UCM‐derived MSC represents an important step towards a GMP compliant large‐scale production platform for these promising cell therapy candidates.     

Functional analysis tools for post‐translational modification: a post‐translational modification database for analysis of proteins and metabolic pathways

Post‐translational modifications (PTMs) are critical regulators of protein function, and nearly 200 different types of PTM have been identified. Advances in high‐resolution mass spectrometry have led to the identification of an unprecedented number of PTM sites in numerous organisms, potentially facilitating a more complete understanding of how PTMs regulate cellular behavior. While databases have been created to house the resulting data, most of these resources focus on individual types of PTM, do not consider quantitative PTM analyses or do not provide tools for the visualization and analysis of PTM data. Here, we describe the Functional Analysis Tools for Post‐Translational Modifications (FAT‐PTM) database ( https://bioinformatics.cse.unr.edu/fat-ptm/ ), which currently supports eight different types of PTM and over 49 000 PTM sites identified in large‐scale proteomic surveys of the model organism Arabidopsis thaliana. The FAT‐PTM database currently supports tools to visualize protein‐centric PTM networks, quantitative phosphorylation site data from over 10 different quantitative phosphoproteomic studies, PTM information displayed in protein‐centric metabolic pathways and groups of proteins that are co‐modified by multiple PTMs. Overall, the FAT‐PTM database provides users with a robust platform to share and visualize experimentally supported PTM data, develop hypotheses related to target proteins or identify emergent patterns in PTM data for signaling and metabolic pathways.     

Metabolic engineering of Escherichia coli for the production of 1,2-propanediol from glycerol

Due to its availability, low‐price, and high degree of reduction, glycerol has become an attractive carbon source for the production of fuels and reduced chemicals. Using the platform we have established from the identification of key pathways mediating fermentative metabolism of glycerol, this work reports the engineering of Escherichia coli for the conversion of glycerol into 1,2‐propanediol (1,2‐PDO). A functional 1,2‐PDO pathway was engineered through a combination of overexpression of genes involved in its synthesis from the key intermediate dihydroxyacetone phosphate (DHAP) and the manipulation of the fermentative glycerol utilization pathway. The former included the overexpression of methylglyoxal synthase (mgsA), glycerol dehydrogenase (gldA), and aldehyde oxidoreductase (yqhD). Manipulation of the glycerol utilization pathway through the replacement of the native E. coli PEP‐dependent dihydroxyacetone kinase (DHAK) with an ATP‐dependent DHAK from C. freundii increased the availability of DHAP allowing for higher 1,2‐PDO production. Analysis of the major fermentative pathways indentified ethanol as a required co‐product while increases in 1,2‐PDO titer and yield were achieved through the disruption of the pathways for acetate and lactate production. Combination of these key metabolic manipulations resulted in an engineered E. coli strain capable of producing 5.6 g/L 1,2‐PDO, at a yield of 21.3% (w/w). This strain also performed well when crude glycerol, a by‐product of biodiesel production, was used as the substrate. The titer and yield achieved in this study were favorable to those obtained with the use of E. coli for the production of 1,2‐PDO from common sugars. Biotechnol. Bioeng. 2011; 108:867–879. © 2010 Wiley Periodicals, Inc.     

Exploring mitochondrial evolution and metabolism organization principles by comparative analysis of metabolic networks

The endosymbiotic theory proposed that mitochondrial genomes are derived from an alpha-proteobacterium-like endosymbiont, which was concluded from sequence analysis. We rebuilt the metabolic networks of mitochondria and 22 relative species, and studied the evolution of mitochondrial metabolism at the level of enzyme content and network topology. Our phylogenetic results based on network alignment and motif identification supported the endosymbiotic theory from the point of view of systems biology for the first time. It was found that the mitochondrial metabolic network were much more compact than the relative species, probably related to the higher efficiency of oxidative phosphorylation of the specialized organelle, and the network is highly clustered around the TCA cycle. Moreover, the mitochondrial metabolic network exhibited high functional specificity to the modules. This work provided insight to the understanding of mitochondria evolution, and the organization principle of mitochondrial metabolic network at the network level.     

Basic and applied uses of genome‐scale metabolic network reconstructions of Escherichia coli

The genome‐scale model (GEM) of metabolism in the bacterium Escherichia coli K‐12 has been in development for over a decade and is now in wide use. GEM‐enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model‐driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome‐scale mechanistic understanding of genotype–phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large‐scale network models with sufficient accuracy.     

A new dynamic model for highly efficient mass transfer in aerated bioreactors and consequences for kLa identification

Gas–liquid mass transfer is often rate‐limiting in laboratory and industrial cultures of aerobic or autotrophic organisms. The volumetric mass transfer coefficient k_La is a crucial characteristic for comparing, optimizing, and upscaling mass transfer efficiency of bioreactors. Reliable dynamic models and resulting methods for parameter identification are needed for quantitative modeling of microbial growth dynamics. We describe a laboratory‐scale stirred tank reactor (STR) with a highly efficient aeration system (k_La ≈ 570 h^?1). The reactor can sustain yeast culture with high cell density and high oxygen uptake rate, leading to a significant drop in gas concentration from inflow to outflow (by 21%). Standard models fail to predict the observed mass transfer dynamics and to identify k_La correctly. In order to capture the concentration gradient in the gas phase, we refine a standard ordinary differential equation (ODE) model and obtain a system of partial integro‐differential equations (PIDE), for which we derive an approximate analytical solution. Specific reactor configurations, in particular a relatively short bubble residence time, allow a quasi steady‐state approximation of the PIDE system by a simpler ODE model which still accounts for the concentration gradient. Moreover, we perform an appropriate scaling of all variables and parameters. In particular, we introduce the dimensionless overall efficiency κ, which is more informative than k_La since it combines the effects of gas inflow, exchange, and solution. Current standard models of mass transfer in laboratory‐scale aerated STRs neglect the gradient in the gas concentration, which arises from highly efficient bubbling systems and high cellular exchange rates. The resulting error in the identification of κ (and hence k_La) increases dramatically with increasing mass transfer efficiency. Notably, the error differs between cell‐free and culture‐based methods of parameter identification, potentially confounding the determination of the “biological enhancement” of mass transfer. Our new model provides an improved theoretical framework that can be readily applied to aerated bioreactors in research and biotechnology. Biotechnol. Bioeng. 2012; 109: 2997–3006. © 2012 Wiley Periodicals, Inc.     

Identification of lncRNA‐associated differential subnetworks in oesophageal squamous cell carcinoma by differential co‐expression analysis

Differential expression analysis has led to the identification of important biomarkers in oesophageal squamous cell carcinoma (ESCC). Despite enormous contributions, it has not harnessed the full potential of gene expression data, such as interactions among genes. Differential co‐expression analysis has emerged as an effective tool that complements differential expression analysis to provide better insight of dysregulated mechanisms and indicate key driver genes. Here, we analysed the differential co‐expression of lncRNAs and protein‐coding genes (PCGs) between normal oesophageal tissue and ESCC tissues, and constructed a lncRNA‐PCG differential co‐expression network (DCN). DCN was characterized as a scale‐free, small‐world network with modular organization. Focusing on lncRNAs, a total of 107 differential lncRNA‐PCG subnetworks were identified from the DCN by integrating both differential expression and differential co‐expression. These differential subnetworks provide a valuable source for revealing lncRNA functions and the associated dysfunctional regulatory networks in ESCC. Their consistent discrimination suggests that they may have important roles in ESCC and could serve as robust subnetwork biomarkers. In addition, two tumour suppressor genes (AL121899.1 and ELMO2), identified in the core modules, were validated by functional experiments. The proposed method can be easily used to investigate differential subnetworks of other molecules in other cancers.     

FunRich proteomics software analysis,let the fun begin!

Protein MS analysis is the preferred method for unbiased protein identification. It is normally applied to a large number of both small‐scale and high‐throughput studies. However, user‐friendly computational tools for protein analysis are still needed. In this issue, Mathivanan and colleagues (Proteomics 2015, 15, 2597–2601) report the development of FunRich software, an open‐access software that facilitates the analysis of proteomics data, providing tools for functional enrichment and interaction network analysis of genes and proteins. FunRich is a reinterpretation of proteomic software, a standalone tool combining ease of use with customizable databases, free access, and graphical representations.     

Genotyping validates photo‐identification by the head scale pattern in a large population of the European adder (Vipera berus)

Capture‐mark‐recapture procedures are a basic tool in population studies and require that individual animals are correctly identified throughout their lifetime. A method that has become more and more popular uses photographic records of natural markings, such as pigmentation pattern and scalation configuration. As with any other marking tool, the validity of the photographic identification technique should be evaluated thoroughly. Here, we report on a large‐scale double‐marking study in which European adders (Vipera berus) were identified by both microsatellite genetic markers and by the pattern of head scalation. Samples that were successfully genotyped for all nine loci yielded 624 unique genotypes, which matched on a one‐to‐one basis with the individual assignments based on the head scalation pattern. Thus, adders considered as different individuals by their genotypes were also identified as different individuals by their head scalation pattern, and vice versa. Overall, variation in the numbers, shape, and arrangement of the head scales enabled us to distinguish among 3200+ photographed individual snakes. Adders that were repeatedly sequenced genetically over intervals of 2–3 years showed no indication whatsoever for a change in the head scale pattern. Photographic records of 900+ adders that were recaptured over periods of up to 12 years showed a very detailed and precise match of the head scale characteristics. These natural marks are thus robust over time and do not change during an individual's lifetime. With very low frequency (0.3%), we detected small changes in scalation that were readily discernible and could be attributed to physical injury or infection. Our study provides a conclusive validation for the use of photo‐identification by head scale patterns in the European adder.     

Development of thermodynamic optimum searching (TOS) to improve the prediction accuracy of flux balance analysis

Flux balance analysis (FBA) has been widely used in calculating steady‐state flux distributions that provide important information for metabolic engineering. Several thermodynamics‐based methods, for example, quantitative assignment of reaction directionality and energy balance analysis have been developed to improve the prediction accuracy of FBA. However, these methods can only generate a thermodynamically feasible range, rather than the most thermodynamically favorable solution. We therefore developed a novel optimization method termed as thermodynamic optimum searching (TOS) to calculate the thermodynamically optimal solution, based on the second law of thermodynamics, the minimum magnitude of the Gibbs free energy change and the maximum entropy production principle (MEPP). Then, TOS was applied to five physiological conditions of Escherichia coli to evaluate its effectiveness. The resulting prediction accuracy was found significantly improved (10.7–48.5%) by comparing with the ¹³C‐fluxome data, indicating that TOS can be considered an advanced calculation and prediction tool in metabolic engineering. Biotechnol. Bioeng. 2013; 110: 914–923. © 2012 Wiley Periodicals, Inc.     

Photographic identification of individuals of a free‐ranging,small terrestrial vertebrate

Recognition of individuals within an animal population is central to a range of estimates about population structure and dynamics. However, traditional methods of distinguishing individuals, by some form of physical marking, often rely on capture and handling which may affect aspects of normal behavior. Photographic identification has been used as a less‐invasive alternative, but limitations in both manual and computer‐automated recognition of individuals are particularly problematic for smaller taxa (<500 g). In this study, we explored the use of photographic identification for individuals of a free‐ranging, small terrestrial reptile using (a) independent observers, and (b) automated matching with the Interactive Individual Identification System (I³S Pattern) computer algorithm. We tested the technique on individuals of an Australian skink in the Egernia group, Slater's skink Liopholis slateri, whose natural history and varied scale markings make it a potentially suitable candidate for photo‐identification. From ‘photographic captures’ of skink head profiles, we designed a multi‐choice key based on alternate character states and tested the abilities of observers — with or without experience in wildlife survey — to identify individuals using categorized test photos. We also used the I³S Pattern algorithm to match the same set of test photos against a database of 30 individuals. Experienced observers identified a significantly higher proportion of photos correctly (74%) than those with no experience (63%) while the I³S software correctly matched 67% as the first ranked match and 83% of images in the top five ranks. This study is one of the first to investigate photo identification with a free‐ranging small vertebrate. The method demonstrated here has the potential to be applied to the developing field of camera‐traps for wildlife survey and thus a wide range of survey and monitoring applications.     

The stimulatory effect of mannitol on levan biosynthesis: Lessons from metabolic systems analysis of Halomonas smyrnensis AAD6T

Halomonas smyrnensis AAD^T is a halophilic, gram‐negative bacterium that can efficiently produce levan from sucrose as carbon source via levansucrase activity. However, systems‐based approaches are required to further enhance its metabolic performance for industrial application. As an important step toward this goal, the genome‐scale metabolic network of Chromohalobacter salexigens DSM3043, which is considered a model organism for halophilic bacteria, has been reconstructed based on its genome annotation, physiological information, and biochemical information. In the present work, the genome‐scale metabolic network of C. salexigens was recruited, and refined via integration of the available biochemical, physiological, and phenotypic features of H. smyrnensis AAD6^T. The generic metabolic model, which comprises 1,393 metabolites and 1,108 reactions, was then systematically analyzed in silico using constraints‐based simulations. To elucidate the relationship between levan biosynthesis and other metabolic processes, an enzyme‐graph representation of the metabolic network and a graph decomposition technique were employed. Using the concept of control effective fluxes, significant links between several metabolic processes and levan biosynthesis were estimated. The major finding was the elucidation of the stimulatory effect of mannitol on levan biosynthesis, which was further verified experimentally via supplementation of mannitol to the fermentation medium. The optimal concentration of 30 g/L mannitol supplemented to the 50 g/L sucrose‐based medium resulted in a twofold increase in levan production in parallel with increased sucrose hydrolysis rate, accumulated extracellular glucose, and decreased fructose uptake rate. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:1386–1397, 2013