Prediction of Neighbor-Dependent Microbial Interactions From Limited Population Data

Modulation of interspecies interactions by the presence of neighbor species is a key ecological factor that governs dynamics and function of microbial communities, yet the development of theoretical frameworks explicit for understanding context-dependent interactions are still nascent. In a recent study, we proposed a novel rule-based inference method termed the Minimal Interspecies Interaction Adjustment (MIIA) that predicts the reorganization of interaction networks in response to the addition of new species such that the modulation in interaction coefficients caused by additional members is minimal. While the theoretical basis of MIIA was established through the previous work by assuming the full availability of species abundance data in axenic, binary, and complex communities, its extension to actual microbial ecology can be highly constrained in cases that species have not been cultured axenically (e.g., due to their inability to grow in the absence of specific partnerships) because binary interaction coefficients – basic parameters required for implementing the MIIA – are inestimable without axenic and binary population data. Thus, here we present an alternative formulation based on the following two central ideas. First, in the case where only data from axenic cultures are unavailable, we remove axenic populations from governing equations through appropriate scaling. This allows us to predict neighbor-dependent interactions in a relative sense (i.e., fractional change of interactions between with versus without neighbors). Second, in the case where both axenic and binary populations are missing, we parameterize binary interaction coefficients to determine their values through a sensitivity analysis. Through the case study of two microbial communities with distinct characteristics and complexity (i.e., a three-member community where all members can grow independently, and a four-member community that contains member species whose growth is dependent on other species), we demonstrated that despite data limitation, the proposed new formulation was able to successfully predict interspecies interactions that are consistent with experimentally derived results. Therefore, this technical advancement enhances our ability to predict context-dependent interspecies interactions in a broad range of microbial systems without being limited to specific growth conditions as a pre-requisite

Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that – in many cases – adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future

Au/TiO2(110) interfacial reconstruction stability from ab initio

We determine the stability and properties of interfaces of low-index Au surfaces adhered to TiO2(110), using density functional theory energy density calculations. We consider Au(100) and Au(111) epitaxies on rutile TiO2(110) surface, as observed in experiments. For each epitaxy, we consider several different interfaces: Au(111)//TiO2(110) and Au(100)//TiO2(110), with and without bridging oxygen, Au(111) on 1x2 added-row TiO2(110) reconstruction, and Au(111) on a proposed 1x2 TiO reconstruction. The density functional theory energy density method computes the energy changes on each of the atoms while forming the interface, and evaluates the work of adhesion to determine the equilibrium interfacial structure.Comment: 20 pages, 11 figure

Paclitaxel plus Carboplatin Chemotherapy for Primary Peritoneal Carcinoma: A Study of 22 Cases and Comparison with Stage III–IV Ovarian Serous Carcinoma

The aim of this study was to assess the clinical characteristics and outcome of patients with either primary peritoneal carcinoma (PPC) or ovarian serous carcinoma (OSC) treated with paclitaxel plus carboplatin chemotherapy. We retrospectively identified 22 PPC patients and 55 stage III–IV OSC patients treated between 2002 and 2007. After exploratory laparotomy, all patients received paclitaxel and carboplatin every 3 weeks, with the goal of optimal cytoreduction. There were no statistically significant differences between the PPC and OSC groups with regard to tumor stage, residual tumor after debulking surgery (initial or interval), serum cancer antigen (CA) 125 levels at diagnosis, and completion of first-line chemotherapy. The progression-free survival (PFS) durations were 12.7 months (95% CI, 6.3–18.5) in the patients with PPC and 15.9 months (95% CI, 13.3–18.5) in those with OSC (p = 0.016). However, the median survival durations were 26.5 months (95% CI, 14.6–38.3) in the patients with PPC and 38 months (95% CI, 23.8–53.8) in those with OSC (p = 0.188). Survival was longer for all patients whose CA125 levels normalized to 26 U/ml during and after treatment. Overall survival (OS) of the patients with PPC was similar to that of the patients with OSC, suggesting that management for advanced-stage OSC would be similar to that for PPC. The combination of optimal debulking with paclitaxel plus carboplatin chemotherapy may offer patients the most effective treatment. The CA125 nadir after cytoreductive surgery can be considered a prognostic factor for OS and PFS in patients with PPC

Homogeneous Gold Catalysis through Relativistic Effects: Addition of Water to Propyne

In the catalytic addition of water to propyne the Au(III) catalyst is not stable under non-relativistic conditions and dissociates into a Au(I) compound and Cl2. This implies that one link in the chain of events in the catalytic cycle is broken and relativity may well be seen as the reason why Au(III) compounds are effective catalysts.Comment: 12 pages, 3 figures, 1 tabl

Population and hierarchy of active species in gold iron oxide catalysts for carbon monoxide oxidation

The identity of active species in supported gold catalysts for low temperature carbon monoxide oxidation remains an unsettled debate. With large amounts of experimental evidence supporting theories of either gold nanoparticles or sub-nm gold species being active, it was recently proposed that a size-dependent activity hierarchy should exist. Here we study the diverging catalytic behaviours after heat treatment of Au/FeOx materials prepared via co-precipitation and deposition precipitation methods. After ruling out any support effects, the gold particle size distributions in different catalysts are quantitatively studied using aberration corrected scanning transmission electron microscopy (STEM). A counting protocol is developed to reveal the true particle size distribution from HAADF-STEM images, which reliably includes all the gold species present. Correlation of the populations of the various gold species present with catalysis results demonstrate that a size-dependent activity hierarchy must exist in the Au/FeOx catalyst

Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that – in many cases – adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future