Microbial interactions shape cheese flavour formation.

Cheese fermentation and flavour formation are the result of complex biochemical reactions driven by the activity of multiple microorganisms. Here, we studied the roles of microbial interactions in flavour formation in a year-long Cheddar cheese making process, using a commercial starter culture containing Streptococcus thermophilus and Lactococcus strains. By using an experimental strategy whereby certain strains were left out from the starter culture, we show that S. thermophilus has a crucial role in boosting Lactococcus growth and shaping flavour compound profile. Controlled milk fermentations with systematic exclusion of single Lactococcus strains, combined with genomics, genome-scale metabolic modelling, and metatranscriptomics, indicated that S. thermophilus proteolytic activity relieves nitrogen limitation for Lactococcus and boosts de novo nucleotide biosynthesis. While S. thermophilus had large contribution to the flavour profile, Lactococcus cremoris also played a role by limiting diacetyl and acetoin formation, which otherwise results in an off-flavour when in excess. This off-flavour control could be attributed to the metabolic re-routing of citrate by L. cremoris from diacetyl and acetoin towards α-ketoglutarate. Further, closely related Lactococcus lactis strains exhibited different interaction patterns with S. thermophilus, highlighting the significance of strain specificity in cheese making. Our results highlight the crucial roles of competitive and cooperative microbial interactions in shaping cheese flavour profile.

The pH-dependent lactose metabolism of Lactobacillus delbrueckii subsp. bulgaricus: An integrative view through a mechanistic computational model.

The fermentation process of milk to yoghurt using Lactobacillus delbrueckii subsp. bulgaricus in co-culture with Streptococcus thermophilus is hallmarked by the breakdown of lactose to organic acids such as lactate. This leads to a substantial decrease in pH - both in the medium, as well as cytosolic. The latter impairs metabolic activities due to the pH-dependence of enzymes, which compromises microbial growth. To quantitatively elucidate the impact of the acidification on metabolism of L. bulgaricus in an integrated way, we have developed a proton-dependent computational model of lactose metabolism and casein degradation based on experimental data. The model accounts for the influence of pH on enzyme activities as well as cellular growth and proliferation of the bacterial population. We used a machine learning approach to quantify the cell volume throughout fermentation. Simulation results show a decrease in metabolic flux with acidification of the cytosol. Additionally, the validated model predicts a similar metabolic behaviour within a wide range of non-limiting substrate concentrations. This computational model provides a deeper understanding of the intricate relationships between metabolic activity and acidification and paves the way for further optimization of yoghurt production under industrial settings.

From genotype to phenotype: computational approaches for inferring microbial traits relevant to the food industry.

When selecting microbial strains for the production of fermented foods, various microbial phenotypes need to be taken into account to achieve target product characteristics, such as biosafety, flavor, texture, and health-promoting effects. Through continuous advances in sequencing technologies, microbial whole-genome sequences of increasing quality can now be obtained both cheaper and faster, which increases the relevance of genome-based characterization of microbial phenotypes. Prediction of microbial phenotypes from genome sequences makes it possible to quickly screen large strain collections in silico to identify candidates with desirable traits. Several microbial phenotypes relevant to the production of fermented foods can be predicted using knowledge-based approaches, leveraging our existing understanding of the genetic and molecular mechanisms underlying those phenotypes. In the absence of this knowledge, data-driven approaches can be applied to estimate genotype-phenotype relationships based on large experimental datasets. Here, we review computational methods that implement knowledge- and data-driven approaches for phenotype prediction, as well as methods that combine elements from both approaches. Furthermore, we provide examples of how these methods have been applied in industrial biotechnology, with special focus on the fermented food industry.

Development of a Tetracycline-Inducible System for Conditional Gene Expression in Lactococcus lactis and Streptococcus thermophilus.

Inducible gene expression systems are invaluable tools for the functional characterization of genes and in the construction of protein overexpression hosts. Controllable expression is especially important for the study of essential and toxic genes or genes where the level of expression tightly influences their cellular effect. Here, we implemented the well-characterized tetracycline-inducible expression system in two industrially important lactic acid bacteria, Lactococcus lactis and Streptococcus thermophilus. Using a fluorescent reporter gene, we show that optimization of the repression level is necessary for efficient induction using anhydrotetracycline in both organisms. Random mutagenesis in the ribosome binding site of the tetracycline repressor TetR in Lactococcus lactis indicated that altering the expression levels of TetR was necessary for efficient inducible expression of the reporter gene. Through this approach, we achieved plasmid-based, inducer-responsive, and tight gene expression in Lactococcus lactis. We then verified the functionality of the optimized inducible expression system in Streptococcus thermophilus following its chromosomal integration using a markerless mutagenesis approach and a novel DNA fragment assembly tool presented herein. This inducible expression system holds several advantages over other described systems in lactic acid bacteria, although more efficient techniques for genetic engineering are still needed to realize these advantages in industrially relevant species, such as S. thermophilus. Our work expands the molecular toolbox of these bacteria, which can accelerate future physiological studies. IMPORTANCE Lactococcus lactis and Streptococcus thermophilus are two industrially important lactic acid bacteria globally used in dairy fermentations and, therefore, are of considerable commercial interest to the food industry. Moreover, due to their general history of safe usage, these microorganisms are increasingly being explored as hosts for the production of heterologous proteins and various chemicals. Development of molecular tools in the form of inducible expression systems and mutagenesis techniques facilitates their in-depth physiological characterization as well as their exploitation in biotechnological applications.

Novel Insights into the Molecular Mechanisms Underlying Robustness and Stability in Probiotic Bifidobacteria.

Some probiotic bifidobacteria are highly robust and shelf-stable, whereas others are difficult to produce, due to their sensitivity to stressors. This limits their potential use as probiotics. Here, we investigate the molecular mechanisms underlying the variability in stress physiologies of Bifidobacterium animalis subsp. lactis BB-12 and Bifidobacterium longum subsp. longum BB-46, by applying a combination of classical physiological characterization and transcriptome profiling. The growth behavior, metabolite production, and global gene expression profiles differed considerably between the strains. BB-12 consistently showed higher expression levels of multiple stress-associated genes, compared to BB-46. This difference, besides higher cell surface hydrophobicity and a lower ratio of unsaturated to saturated fatty acids in the cell membrane of BB-12, should contribute to its higher robustness and stability. In BB-46, the expression of genes related to DNA repair and fatty acid biosynthesis was higher in the stationary than in the exponential phase, which was associated with enhanced stability of BB-46 cells harvested in the stationary phase. The results presented herein highlight important genomic and physiological features contributing to the stability and robustness of the studied Bifidobacterium strains. IMPORTANCE Probiotics are industrially and clinically important microorganisms. To exert their health-promoting effects, probiotic microorganisms must be administered at high counts, while maintaining their viability at the time of consumption. In addition, intestinal survival and bioactivity are important criteria for probiotics. Although bifidobacteria are among the most well-documented probiotics, the industrial-scale production and commercialization of some Bifidobacterium strains is challenged by their high sensitivity to environmental stressors encountered during manufacturing and storage. Through a comprehensive comparison of the metabolic and physiological characteristics of 2 Bifidobacterium strains, we identify key biological markers that can serve as indicators for robustness and stability in bifidobacteria.

A Two-Compartment Fermentation System to Quantify Strain-Specific Interactions in Microbial Co-Cultures.

To fulfil the growing interest in investigating microbial interactions in co-cultures, a novel two-compartment bioreactor system was developed, characterised, and implemented. The system allowed for the exchange of amino acids and peptides via a polyethersulfone membrane that retained biomass. Further system characterisation revealed a Bodenstein number of 18, which hints at backmixing. Together with other physical settings, the existence of unwanted inner-compartment substrate gradients could be ruled out. Furthermore, the study of Damkoehler numbers indicated that a proper metabolite supply between compartments was enabled. Implementing the two-compartment system (2cs) for growing Streptococcus thermophilus and Lactobacillus delbrueckii subs. bulgaricus, which are microorganisms commonly used in yogurt starter cultures, revealed only a small variance between the one-compartment and two-compartment approaches. The 2cs enabled the quantification of the strain-specific production and consumption rates of amino acids in an interacting S. thermophilus-L. bulgaricus co-culture. Therefore, comparisons between mono- and co-culture performance could be achieved. Both species produce and release amino acids. Only alanine was produced de novo from glucose through potential transaminase activity by L. bulgaricus and consumed by S. thermophilus. Arginine availability in peptides was limited to S. thermophilus' growth, indicating active biosynthesis and dependency on the proteolytic activity of L. bulgaricus. The application of the 2cs not only opens the door for the quantification of exchange fluxes between microbes but also enables continuous production modes, for example, for targeted evolution studies.

Ethanol-lactate transition of Lachancea thermotolerans is linked to nitrogen metabolism.

Climate change increases sugar content in grapes, resulting in unwanted increase in ethanol content of wine. Lachancea thermotolerans ferments glucose and fructose into both ethanol and lactate, decreasing final ethanol content and positively affecting wine acidity. Reported Lachancea thermotolerans strains show big variation in lactate production during fermentation. However, a mechanistic understanding of this lactate producing phenotype is currently lacking. Through a combination of metabolomics, transcriptomics, genomics and computational methods we show that the lactate production is induced by amino acid limitation in a high lactate producing strain. We found in fermentations in synthetic grape juice media that lactate production starts in the last stages of growth, marked by decreased growth rate and increased expression levels of stress related genes. This onset of lactate production is specific for the high lactate producing strain and independent of oxygen availability. The onset of lactate production was changed by increased amino acid content of the media, and it is shown by both computational methods and amino acid measurements that at the onset of lactate production amino acids become limiting for growth. This study shows that lactate production of Lachancea thermotolerans is directly linked to nitrogen availability in the media, an insight that can further aid in the improvement of wine quality.

Stress Response in Bifidobacteria.

Bifidobacteria naturally inhabit diverse environments, including the gastrointestinal tracts of humans and animals. Members of the genus are of considerable scientific interest due to their beneficial effects on health and, hence, their potential to be used as probiotics. By definition, probiotic cells need to be viable despite being exposed to several stressors in the course of their production, storage, and administration. Examples of common stressors encountered by probiotic bifidobacteria include oxygen, acid, and bile salts. As bifidobacteria are highly heterogenous in terms of their tolerance to these stressors, poor stability and/or robustness can hamper the industrial-scale production and commercialization of many strains. Therefore, interest in the stress physiology of bifidobacteria has intensified in recent decades, and many studies have been established to obtain insights into the molecular mechanisms underlying their stability and robustness. By complementing traditional methodologies, omics technologies have opened new avenues for enhancing the understanding of the defense mechanisms of bifidobacteria against stress. In this review, we summarize and evaluate the current knowledge on the multilayered responses of bifidobacteria to stressors, including the most recent insights and hypotheses. We address the prevailing stressors that may affect the cell viability during production and use as probiotics. Besides phenotypic effects, molecular mechanisms that have been found to underlie the stress response are described. We further discuss strategies that can be applied to improve the stability of probiotic bifidobacteria and highlight knowledge gaps that should be addressed in future studies.

Differential Amino Acid Uptake and Depletion in Mono-Cultures and Co-Cultures of Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus in a Novel Semi-Synthetic Medium.

The mechanistic understanding of the physiology and interactions of microorganisms in starter cultures is critical for the targeted improvement of fermented milk products, such as yogurt, which is produced by Streptococcus thermophilus in co-culture with Lactobacillus delbrueckii subsp. bulgaricus. However, the use of complex growth media or milk is a major challenge for quantifying metabolite production, consumption, and exchange in co-cultures. This study developed a synthetic medium that enables the establishment of defined culturing conditions and the application of flow cytometry for measuring species-specific biomass values. Time courses of amino acid concentrations in mono-cultures and co-cultures of L. bulgaricus ATCC BAA-365 with the proteinase-deficient S. thermophilus LMG 18311 and with a proteinase-positive S. thermophilus strain were determined. The analysis revealed that amino acid release rates in co-culture were not equivalent to the sum of amino acid release rates in mono-cultures. Data-driven and pH-dependent amino acid release models were developed and applied for comparison. Histidine displayed higher concentrations in co-cultures, whereas isoleucine and arginine were depleted. Amino acid measurements in co-cultures also confirmed that some amino acids, such as lysine, are produced and then consumed, thus being suitable candidates to investigate the inter-species interactions in the co-culture and contribute to the required knowledge for targeted shaping of yogurt qualities.

Genome-Scale Metabolic Modeling Combined with Transcriptome Profiling Provides Mechanistic Understanding of Streptococcus thermophilus CH8 Metabolism.

Streptococcus thermophilus is a lactic acid bacterium adapted toward growth in milk and is a vital component of starter cultures for milk fermentation. Here, we combine genome-scale metabolic modeling and transcriptome profiling to obtain novel metabolic insights into this bacterium. Notably, a refined genome-scale metabolic model (GEM) accurately representing S. thermophilus CH8 metabolism was developed. Modeling the utilization of casein as a nitrogen source revealed an imbalance in amino acid supply and demand, resulting in growth limitation due to the scarcity of specific amino acids, in particular sulfur amino acids. Growth experiments in milk corroborated this finding. A subtle interdependency of the redox balance and the secretion levels of the key metabolites lactate, formate, acetoin, and acetaldehyde was furthermore identified with the modeling approach, providing a mechanistic understanding of the factors governing the secretion product profile. As a potential effect of high expression of arginine biosynthesis genes, a moderate secretion of ornithine was observed experimentally, augmenting the proposed hypothesis of ornithine/putrescine exchange as part of the protocooperative interaction between S. thermophilus and Lactobacillus delbrueckii subsp. bulgaricus in yogurt. This study provides a foundation for future community modeling of food fermentations and rational development of starter strains with improved functionality. IMPORTANCE Streptococcus thermophilus is one the main organisms involved in the fermentation of milk and, increasingly, also in the fermentation of plant-based foods. The construction of a functional high-quality genome-scale metabolic model, in conjunction with in-depth transcriptome profiling with a focus on metabolism, provides a valuable resource for the improved understanding of S. thermophilus physiology. An example is the model-based prediction of the most significant route of synthesis for the characteristic yogurt flavor compound acetaldehyde and identification of metabolic principles governing the synthesis of other flavor compounds. Moreover, the systematic assessment of amino acid supply and demand during growth in milk provides insights into the key challenges related to nitrogen metabolism that is imposed on S. thermophilus and any other organism associated with the milk niche.

Genome-Wide Assessment of Stress-Associated Genes in Bifidobacteria.

Over the last decade, the genomes of several Bifidobacterium strains have been sequenced, delivering valuable insights into their genetic makeup. However, bifidobacterial genomes have not yet been systematically mined for genes associated with stress response functions and their regulation. In this work, a list of 76 genes related to stress response in bifidobacteria was compiled from previous studies. The prevalence of the genes was evaluated among the genome sequences of 171 Bifidobacterium strains. Although genes of the protein quality control and DNA repair systems appeared to be highly conserved, genome-wide in silico screening for consensus sequences of putative regulators suggested that the regulation of these systems differs among phylogenetic groups. Homologs of multiple oxidative stress-associated genes are shared across species, albeit at low sequence similarity. Bee isolates were confirmed to harbor unique genetic features linked to oxygen tolerance. Moreover, most studied Bifidobacterium adolescentis and all Bifidobacterium angulatum strains lacked a set of reactive oxygen species-detoxifying enzymes, which might explain their high sensitivity to oxygen. Furthermore, the presence of some putative transcriptional regulators of stress responses was found to vary across species and strains, indicating that different regulation strategies of stress-associated gene transcription contribute to the diverse stress tolerance. The presented stress response gene profiles of Bifidobacterium strains provide a valuable knowledge base for guiding future studies by enabling hypothesis generation and the identification of key genes for further analyses. IMPORTANCE Bifidobacteria are Gram-positive bacteria that naturally inhabit diverse ecological niches, including the gastrointestinal tract of humans and animals. Strains of the genus Bifidobacterium are widely used as probiotics, since they have been associated with health benefits. In the course of their production and administration, probiotic bifidobacteria are exposed to several stressors that can challenge their survival. The stress tolerance of probiotic bifidobacteria is, therefore, an important selection criterion for their commercial application, since strains must maintain their viability to exert their beneficial health effects. As the ability to cope with stressors varies among Bifidobacterium strains, comprehensive understanding of the underlying stress physiology is required for enabling knowledge-driven strain selection and optimization of industrial-scale production processes.

Identifying the essential nutritional requirements of the probiotic bacteria Bifidobacterium animalis and Bifidobacterium longum through genome-scale modeling.

Although bifidobacteria are widely used as probiotics, their metabolism and physiology remain to be explored in depth. In this work, strain-specific genome-scale metabolic models were developed for two industrially and clinically relevant bifidobacteria, Bifidobacterium animalis subsp. lactis BB-12® and B. longum subsp. longum BB-46, and subjected to iterative cycles of manual curation and experimental validation. A constraint-based modeling framework was used to probe the metabolic landscape of the strains and identify their essential nutritional requirements. Both strains showed an absolute requirement for pantethine as a precursor for coenzyme A biosynthesis. Menaquinone-4 was found to be essential only for BB-46 growth, whereas nicotinic acid was only required by BB-12®. The model-generated insights were used to formulate a chemically defined medium that supports the growth of both strains to the same extent as a complex culture medium. Carbohydrate utilization profiles predicted by the models were experimentally validated. Furthermore, model predictions were quantitatively validated in the newly formulated medium in lab-scale batch fermentations. The models and the formulated medium represent valuable tools to further explore the metabolism and physiology of the two species, investigate the mechanisms underlying their health-promoting effects and guide the optimization of their industrial production processes.

Updated Genome Sequence for the Probiotic Bacterium Bifidobacterium animalis subsp. lactis BB-12.

The genome of Bifidobacterium animalis subsp. lactis BB-12 was sequenced using Oxford Nanopore Technologies long-read and Illumina short-read sequencing platforms. A hybrid genome assembly approach was used to construct an updated complete genome sequence for BB-12 containing 1,944,152 bp, with a G+C content of 60.5% and 1,615 genes.

Harnessing the metabolic potential of Streptococcus thermophilus for new biotechnological applications.

Streptococcus thermophilus is a microorganism extensively used in cheese and yogurt fermentation. Its economic value, combined with an increasing demand for novel starter cultures with improved functionality, foster numerous research efforts to unravel key aspects of S. thermophilus physiology. Several phenotypic traits are linked to industrial applications. These include sugar metabolism, proteolysis and the production of important metabolites such as acetaldehyde, exopolysaccharides, and vitamins, which affect the organoleptic properties of fermented foods and protocooperation with Lactobacillus delbrueckii subsp. bulgaricus. The advent of new molecular tools including a genome editing toolbox facilitates engineering S. thermophilus for physiological studies as well as generating strains with improved technological and/or functional characteristics.

A comparative genomics approach for identifying host-range determinants in Streptococcus thermophilus bacteriophages.

Comparative genomics has proven useful in exploring the biodiversity of phages and understanding phage-host interactions. This knowledge is particularly useful for phages infecting Streptococcus thermophilus, as they constitute a constant threat during dairy fermentations. Here, we explore the genetic diversity of S. thermophilus phages to identify genetic determinants with a signature for host specificity, which could be linked to the bacterial receptor genotype. A comparative genomic analysis was performed on 142 S. thermophilus phage genomes, 55 of which were sequenced in this study. Effectively, 94 phages were assigned to the group cos (DT1), 36 to the group pac (O1205), six to the group 5093, and six to the group 987. The core genome-based phylogeny of phages from the two dominating groups and their receptor binding protein (RBP) phylogeny corresponded to the phage host-range. A role of RBP in host recognition was confirmed by constructing a fluorescent derivative of the RBP of phage CHPC951, followed by studying the binding of the protein to the host strain. Furthermore, the RBP phylogeny of the cos group was found to correlate with the host genotype of the exocellular polysaccharide-encoding operon. These findings provide novel insights towards developing strategies to combat phage infections in dairies.

Putative antibiotic resistance genes present in extant Bacillus licheniformis and Bacillus paralicheniformis strains are probably intrinsic and part of the ancient resistome.

Whole-genome sequencing and phenotypic testing of 104 strains of Bacillus licheniformis and Bacillus paralicheniformis from a variety of sources and time periods was used to characterize the genetic background and evolution of (putative) antimicrobial resistance mechanisms. Core proteins were identified in draft genomes and a phylogenetic analysis based on single amino acid polymorphisms allowed the species to be separated into two phylogenetically distinct clades with one outlier. Putative antimicrobial resistance genes were identified and mapped. A chromosomal ermD gene was found at the same location in all B. paralichenformis and in 27% of B. licheniformis genomes. Erythromycin resistance correlated very well with the presence of ermD. The putative streptomycin resistance genes, aph and aadK, were found in the chromosome of all strains as adjacent loci. Variations in amino acid sequence did not correlate with streptomycin susceptibility although the species were less susceptible than other Bacillus species. A putative chloramphenicol resistance gene (cat), encoding a novel chloramphenicol acetyltransferase protein was also found in the chromosome of all strains. Strains encoding a truncated CAT protein were sensitive to chloramphenicol. For all four resistance genes, the diversity and genetic context followed the overall phylogenetic relationship. No potentially mobile genetic elements were detected in their vicinity. Moreover, the genes were only distantly related to previously-described cat, aph, aad and erm genes present on mobile genetic elements or in other species. Thus, these genes are suggested to be intrinsic to B. licheniformis and B. paralicheniformis and part of their ancient resistomes. Since there is no evidence supporting horizontal transmission, these genes are not expected to add to the pool of antibiotic resistance elements considered to pose a risk to human or animal health. Whole-genome based phylogenetic and sequence analysis, combined with phenotypic testing, is proposed to be suitable for determining intrinsic resistance and evolutionary relationships.

MARSI: metabolite analogues for rational strain improvement.

Summary: Metabolite analogues (MAs) mimic the structure of native metabolites, can competitively inhibit their utilization in enzymatic reactions, and are commonly used as selection tools for isolating desirable mutants of industrial microorganisms. Genome-scale metabolic models representing all biochemical reactions in an organism can be used to predict effects of MAs on cellular phenotypes. Here, we present the metabolite analogues for rational strain improvement (MARSI) framework. MARSI provides a rational approach to strain improvement by searching for metabolites as targets instead of genes or reactions. The designs found by MARSI can be implemented by supplying MAs in the culture media, enabling metabolic rewiring without the use of recombinant DNA technologies that cannot always be used due to regulations. To facilitate experimental implementation, MARSI provides tools to identify candidate MAs to a target metabolite from a database of known drugs and analogues. Availability and implementation: The code is freely available at https://github.com/biosustain/marsi under the Apache License V2. MARSI is implemented in Python. Supplementary information: Supplementary data are available at Bioinformatics online.

Constraint-based modeling in microbial food biotechnology.

Genome-scale metabolic network reconstruction offers a means to leverage the value of the exponentially growing genomics data and integrate it with other biological knowledge in a structured format. Constraint-based modeling (CBM) enables both the qualitative and quantitative analyses of the reconstructed networks. The rapid advancements in these areas can benefit both the industrial production of microbial food cultures and their application in food processing. CBM provides several avenues for improving our mechanistic understanding of physiology and genotype-phenotype relationships. This is essential for the rational improvement of industrial strains, which can further be facilitated through various model-guided strain design approaches. CBM of microbial communities offers a valuable tool for the rational design of defined food cultures, where it can catalyze hypothesis generation and provide unintuitive rationales for the development of enhanced community phenotypes and, consequently, novel or improved food products. In the industrial-scale production of microorganisms for food cultures, CBM may enable a knowledge-driven bioprocess optimization by rationally identifying strategies for growth and stability improvement. Through these applications, we believe that CBM can become a powerful tool for guiding the areas of strain development, culture development and process optimization in the production of food cultures. Nevertheless, in order to make the correct choice of the modeling framework for a particular application and to interpret model predictions in a biologically meaningful manner, one should be aware of the current limitations of CBM.

Polysaccharide production by lactic acid bacteria: from genes to industrial applications.

The ability to produce polysaccharides with diverse biological functions is widespread in bacteria. In lactic acid bacteria (LAB), production of polysaccharides has long been associated with the technological, functional and health-promoting benefits of these microorganisms. In particular, the capsular polysaccharides and exopolysaccharides have been implicated in modulation of the rheological properties of fermented products. For this reason, screening and selection of exocellular polysaccharide-producing LAB has been extensively carried out by academia and industry. To further exploit the ability of LAB to produce polysaccharides, an in-depth understanding of their biochemistry, genetics, biosynthetic pathways, regulation and structure-function relationships is mandatory. Here, we provide a critical overview of the latest advances in the field of glycosciences in LAB. Surprisingly, the understanding of the molecular processes involved in polysaccharide synthesis is lagging behind, and has not accompanied the increasing commercial value and application potential of these polymers. Seizing the natural diversity of polysaccharides for exciting new applications will require a concerted effort encompassing in-depth physiological characterization of LAB at the systems level. Combining high-throughput experimentation with computational approaches, biochemical and structural characterization of the polysaccharides and understanding of the structure-function-application relationships is essential to achieve this ambitious goal.

Trash to treasure: production of biofuels and commodity chemicals via syngas fermenting microorganisms.

Fermentation of syngas is a means through which unutilized organic waste streams can be converted biologically into biofuels and commodity chemicals. Despite recent advances, several issues remain which limit implementation of industrial-scale syngas fermentation processes. At the cellular level, the energy conservation mechanism of syngas fermenting microorganisms has not yet been entirely elucidated. Furthermore, there was a lack of genetic tools to study and ultimately enhance their metabolic capabilities. Recently, substantial progress has been made in understanding the intricate energy conservation mechanisms of these microorganisms. Given the complex relationship between energy conservation and metabolism, strain design greatly benefits from systems-level approaches. Numerous genetic manipulation tools have also been developed, paving the way for the use of metabolic engineering and systems biology approaches. Rational strain designs can now be deployed resulting in desirable phenotypic traits for large-scale production.