Managing ecosystems to maintain biodiversity may be one approach to ensuring their dynamic stability, productivity, and delivery of vital services. The applicability of this approach to industrial ecosystems that harness the metabolic activities of microbes has been proposed but has never been tested at relevant scales. We used a tag-sequencing approach with bacterial small subunit rRNA (16S) genes and eukaryotic internal transcribed spacer 2 (ITS2) to measuring the taxonomic composition and diversity of bacteria and eukaryotes in an open pond managed for bioenergy production by microalgae over a year. Periods of high eukaryotic diversity were associated with high and more-stable biomass productivity. In addition, bacterial diversity and eukaryotic diversity were inversely correlated over time, possibly due to their opposite responses to temperature. The results indicate that maintaining diverse communities may be essential to engineering stable and productive bioenergy ecosystems using microorganisms.
Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat's signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81-99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.
BackgroundComposition of the vaginal microbiota has significant influence on female urogenital health and control of infectious disease. Murine models are widely utilized to characterize host-pathogen interactions within the vaginal tract, however, the composition of endogenous vaginal flora remains largely undefined with modern microbiome analyses. Here, we employ 16S rRNA amplicon sequencing to establish the native microbial composition of the vaginal tract in adult C57Bl/6 J mice. We further interrogate the impact of estrous cycle and introduction of the human vaginal pathobiont, group B Streptococcus (GBS) on community state type and stability, and conversely, the impact of the vaginal microbiota on GBS persistence.
ResultsSequencing analysis revealed five distinctive community states of the vaginal microbiota dominated largely by Staphylococcus and/or Enterococcus, Lactobacillus, or a mixed population. Stage of estrus did not impact microbial composition. Introduction of GBS decreased community stability at early timepoints; and in some mice, GBS became the dominant bacterium by day 21. Endogenous Staphylococcus abundance correlated with GBS ascension into the uterus, and increased community stability in GBS-challenged mice.
ConclusionsThe murine vaginal flora is diverse and fluctuates independently of the estrous cycle. Endogenous flora may impact pathogen colonization and dissemination and should be considered in urogenital infection models.
This report presents research into a fundamentally new approach to finding all pairwise minimum cuts in a network that can utilize optimality conditions other than those characterized by Mengers theorem or the max-flow min-cut theorem. The focus is on vertex degree domination, rather than construction of saturating paths. We have not been able to show a polynomial-time, deterministic algorithm of this kind, but the investigation has yielded many new insights into the structure of minimum cuts in a network and heuristics for discovering them.
Pre-2018 CSE ID: CS1999-0625
This report describes an optimization problem called a minimax program that is similar to a linear program, except that the addition operator is replaced by the maximum operator in the constraint inequalities. The relation of this problem to some well-known problems is clarified. An interesting special case, bitonic columns, is identified, and a new, efficient algorithm is presented for its solution. Also presented is an efficient algortihm for recognition of matrices with the bitonic columns property, which is an extension of the PQ-tree reduction algorithm.
Pre-2018 CSE ID: CS1999-0624
Proof-carrying code is a technique that can be used to execute untrusted code safely. A code consumer specifies requirements and safety rules which define the safe behavior of a system, and a code producer packages each program with a formal proof that the program satisfies the requirements. The consumer uses a fast proof validator to check that the proof is correct, and hence the program is safe. In this report, we discuss applications for which proof-carrying code is appropriate, explain the mechanics of proof-carrying code, compare it with other security techniques and propose research directions for the method.
Pre-2018 CSE ID: CS1999-0633