PGASO: A synthetic biology tool for engineering a cellulolytic yeast

ABSTRACT: BACKGROUND: To achieve an economical cellulosic ethanol production, a host that can do both cellulosic saccharification and ethanol fermentation is desirable. However, to engineer a non-cellulolytic yeast to be such a host requires synthetic biology techniques to transform multiple enzyme genes into its genome. RESULTS: A technique, named Promoter-based Gene Assembly and Simultaneous Overexpression (PGASO), that employs overlapping oligonucleotides for recombinatorial assembly of gene cassettes with individual promoters, was developed. PGASO was applied to engineer Kluyveromycesmarxianus KY3, which is a thermo- and toxin-tolerant yeast. We obtained a recombinant strain, called KR5, that is capable of simultaneously expressing exoglucanase and endoglucanase (both of Trichodermareesei), a beta-glucosidase (from a cow rumen fungus), a neomycin phosphotransferase, and a green fluorescent protein. High transformation efficiency and accuracy were achieved as ~63% of the transformants was confirmed to be correct. KR5 can utilize beta-glycan, cellobiose or CMC as the sole carbon source for growth and can directly convert cellobiose and beta-glycan to ethanol. CONCLUSIONS: This study provides the first example of multi-gene assembly in a single step in a yeast species other than Saccharomyces cerevisiae. We successfully engineered a yeast host with a five-gene cassette assembly and the new host is capable of co-expressing three types of cellulase genes. Our study shows that PGASO is an efficient tool for simultaneous expression of multiple enzymes in the kefir yeast KY3 and that KY3 can serve as a host for developing synthetic biology tools.     

A framework for evolutionary systems biology

Background  

Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.     

Toward a conceptual framework for biology

Science progresses faster when researchers operate within an explicit framework of concepts and theories, but currently biology has no explicit, overarching conceptual framework and few general theories. The single general theory currently recognized is that of evolution, which was put forth by Charles Darwin 150 years ago. Recently, Scheiner and Willig (2008) explicated a similarly general theory of ecology. In this paper, using the theory of evolution as an exemplar, I discuss the nature of theory in biology and put forth an overarching theory, as well as new general theories for cells, organisms, and genetics. Along with the theories of evolution and ecology, these constitute a general conceptual framework for the biological sciences. This framework reveals linkages among the various parts of biology, makes explicit the assumptions behind more narrow theories and models, and provides new insights into the structures of biological theories. This framework can also be used as a teaching tool, moving the teaching of biology beyond the transference of a vast compendium of facts. My hope is that this essay will lead to a vigorous discussion and debate across all of biology about the nature and structure of its theories.     

A hierarchical bayesian approach to ecological count data: a flexible tool for ecologists

Many ecological studies use the analysis of count data to arrive at biologically meaningful inferences. Here, we introduce a hierarchical bayesian approach to count data. This approach has the advantage over traditional approaches in that it directly estimates the parameters of interest at both the individual-level and population-level, appropriately models uncertainty, and allows for comparisons among models, including those that exceed the complexity of many traditional approaches, such as ANOVA or non-parametric analogs. As an example, we apply this method to oviposition preference data for butterflies in the genus Lycaeides. Using this method, we estimate the parameters that describe preference for each population, compare the preference hierarchies among populations, and explore various models that group populations that share the same preference hierarchy.     

A biomolecular isolation framework for eco-systems biology

Mixed microbial communities are complex, dynamic and heterogeneous. It is therefore essential that biomolecular fractions obtained for high-throughput omic analyses are representative of single samples to facilitate meaningful data integration, analysis and modeling. We have developed a new methodological framework for the reproducible isolation of high-quality genomic DNA, large and small RNA, proteins, and polar and non-polar metabolites from single unique mixed microbial community samples. The methodology is based around reproducible cryogenic sample preservation and cell lysis. Metabolites are extracted first using organic solvents, followed by the sequential isolation of nucleic acids and proteins using chromatographic spin columns. The methodology was validated by comparison to traditional dedicated and simultaneous biomolecular isolation methods. To prove the broad applicability of the methodology, we applied it to microbial consortia of biotechnological, environmental and biomedical research interest. The developed methodological framework lays the foundation for standardized molecular eco-systematic studies on a range of different microbial communities in the future.     

Least-inclusive taxonomic unit: a new taxonomic concept for biology

Phylogenetic taxonomy has been introduced as a replacement for the Linnaean system. It differs from traditional nomenclature in defining taxon names with reference to phylogenetic trees and in not employing ranks for supraspecific taxa. However, 'species' are currently kept distinct. Within a system of phylogenetic taxonomy we believe that taxon names should refer to monophyletic groups only and that species should not be recognized as taxa. To distinguish the smallest identified taxa, we here introduce the least-inclusive taxonomic unit (LITU), which are differentiated from more inclusive taxa by initial lower-case letters. LITUs imply nothing absolute about inclusiveness, only that subdivisions are not presently recognized.     

Toward a stoichiometric framework for evolutionary biology

Ecological stoichiometry, the study of the balance of energy and materials in living systems, may serve as a useful synthetic framework for evolutionary biology. Here, we review recent work that illustrates the power of a stoichiometric approach to evolution across multiple scales, and then point to important open questions that may chart the way forward in this new field. At the molecular level, stoichiometry links hereditary changes in the molecular composition of organisms to key phenotypic functions. At the level of evolutionary ecology, a simultaneous focus on the energetic and material underpinnings of evolutionary tradeoffs and transactions highlights the relationship between the cost of resource acquisition and the functional consequences of biochemical composition. At the macroevolutionary level, a stoichiometric perspective can better operationalize models of adaptive radiation and escalation, and elucidate links between evolutionary innovation and the development of global biogeochemical cycles. Because ecological stoichiometry focuses on the interaction of energetic and multiple material currencies, it should provide new opportunities for coupling evolutionary dynamics across scales from genomes to the biosphere.     

The metacommunity concept: a framework for multi-scale community ecology

The metacommunity concept is an important way to think about linkages between different spatial scales in ecology. Here we review current understanding about this concept. We first investigate issues related to its definition as a set of local communities that are linked by dispersal of multiple potentially interacting species. We then identify four paradigms for metacommunities: the patch‐dynamic view, the species‐sorting view, the mass effects view and the neutral view, that each emphasizes different processes of potential importance in metacommunities. These have somewhat distinct intellectual histories and we discuss elements related to their potential future synthesis. We then use this framework to discuss why the concept is useful in modifying existing ecological thinking and illustrate this with a number of both theoretical and empirical examples. As ecologists strive to understand increasingly complex mechanisms and strive to work across multiple scales of spatio‐temporal organization, concepts like the metacommunity can provide important insights that frequently contrast with those that would be obtained with more conventional approaches based on local communities alone.     

A hierarchical modeling framework for multiple observer transect surveys

Ecologists often use multiple observer transect surveys to census animal populations. In addition to animal counts, these surveys produce sequences of detections and non-detections for each observer. When combined with additional data (i.e. covariates such as distance from the transect line), these sequences provide the additional information to estimate absolute abundance when detectability on the transect line is less than one. Although existing analysis approaches for such data have proven extremely useful, they have some limitations. For instance, it is difficult to extrapolate from observed areas to unobserved areas unless a rigorous sampling design is adhered to; it is also difficult to share information across spatial and temporal domains or to accommodate habitat-abundance relationships. In this paper, we introduce a hierarchical modeling framework for multiple observer line transects that removes these limitations. In particular, abundance intensities can be modeled as a function of habitat covariates, making it easier to extrapolate to unsampled areas. Our approach relies on a complete data representation of the state space, where unobserved animals and their covariates are modeled using a reversible jump Markov chain Monte Carlo algorithm. Observer detections are modeled via a bivariate normal distribution on the probit scale, with dependence induced by a distance-dependent correlation parameter. We illustrate performance of our approach with simulated data and on a known population of golf tees. In both cases, we show that our hierarchical modeling approach yields accurate inference about abundance and related parameters. In addition, we obtain accurate inference about population-level covariates (e.g. group size). We recommend that ecologists consider using hierarchical models when analyzing multiple-observer transect data, especially when it is difficult to rigorously follow pre-specified sampling designs. We provide a new R package, hierarchicalDS, to facilitate the building and fitting of these models.     

生物学概念教学策略初探

生物学概念的教学是生物学教学的一项重要任务。在具体的生物学概念教学实践中,教师采用的教学策略风格各异,但就其共性来说,生物学概念的教学策略一般由五个层次性的环节组成。本文就这五个萃知理论,结合教学实践作一些探讨。     

Towards a functional resource-based concept for habitat: a butterfly biology viewpoint

The habitat is the basic unit for developments in life history, population dynamics, landscape ecology and conservation of organisms. It is frequently treated as a particulate, invariant and homogeneous entity (a patch). Here we examine the implications of using this concept of habitat in butterfly biology. In doing so, we suggest the alternative approach of applying a functional resource-based concept of habitat. This recognises the fundamental requirements of organisms, consumables and utilities, the latter describing suitable environmental conditions as well as essential substrates. We argue that a resource-based concept is critical for butterfly conservation and call for the development of a resource database on butterfly biology .     

A semiotic framework for evolutionary and developmental biology

This work aims at constructing a semiotic framework for an expanded evolutionary synthesis grounded on Peirce's universal categories and the six space/time/function relations [Taborsky, E., 2004. The nature of the sign as a WFF--a well-formed formula, SEED J. (Semiosis Evol. Energy Dev.) 4 (4), 5-14] that integrate the Lamarckian (internal/external) and Darwinian (individual/population) cuts. According to these guide lines, it is proposed an attempt to formalize developmental systems theory by using the notion of evolving developing agents (EDA) that provides an internalist model of a general transformative tendency driven by organism's need to cope with environmental uncertainty. Development and evolution are conceived as non-programmed open-ended processes of information increase where EDA reach a functional compromise between: (a) increments of phenotype's uniqueness (stability and specificity) and (b) anticipation to environmental changes. Accordingly, changes in mutual information content between the phenotype/environment drag subsequent changes in mutual information content between genotype/phenotype and genotype/environment at two interwoven scales: individual life cycle (ontogeny) and species time (phylogeny), respectively. Developmental terminal additions along with increment minimization of developmental steps must be positively selected.     

Stem-loop oligonucleotides: a robust tool for molecular biology and biotechnology

The specific structural features of stem-loop (hairpin) DNA constructs provide increased specificity of target recognition. Recently, several robust assays have been developed that exploit the potential of structurally constrained oligonucleotides to hybridize with their cognate targets. Here, I review new diagnostic approaches based on the formation of stem-loop DNA oligonucleotides: molecular beacon methodology, suppression PCR approaches and the use of hairpin probes in DNA microarrays. The advantages of these techniques over existing ones for sequence-specific DNA detection, amplification and manipulation are discussed.     

Kleisli: a new tool for data integration in biology.

One of the central problems in bioinformatics is data retrieval and integration. The existing biological databases are geographically distributed across the Internet, complex and heterogeneous in data types and data structures, and constantly changing. With the current rapid growth of biomedical data, the challenge is how large volumes of data retrieved from multiple databases can be transformed and integrated automatically and flexibly. This article describes a powerful new tool, the Kleisli system, for complex queries across multiple databases and data integration.     

The Poisson-Boltzmann equation for biomolecular electrostatics: a tool for structural biology

Electrostatics plays a fundamental role in virtually all processes involving biomolecules in solution. The Poisson-Boltzmann equation constitutes one of the most fundamental approaches to treat electrostatic effects in solution. The theoretical basis of the Poisson-Boltzmann equation is reviewed and a wide range of applications is presented, including the computation of the electrostatic potential at the solvent-accessible molecular surface, the computation of encounter rates between molecules in solution, the computation of the free energy of association and its salt dependence, the study of pKa shifts and the combination with classical molecular mechanics and dynamics. Theoretical results may be used for rationalizing or predicting experimental results, or for suggesting working hypotheses. An ever-increasing body of successful applications proves that the Poisson-Boltzmann equation is a useful tool for structural biology and complementary to other established experimental and theoretical methodologies.