scholarly journals Regularized S-Map Reveals Varying Bacterial Interactions

2020 ◽  
Vol 86 (20) ◽  
Author(s):  
Zhong Yu ◽  
Zhihao Gan ◽  
Hao Huang ◽  
Yuelan Zhu ◽  
Fangang Meng
Keyword(s):  
Bacterial Community ◽  
Structural Stability ◽  
Interspecific Interactions ◽  
Treatment Plant ◽  
Series Data ◽  
Control Group ◽  
Endogenous Respiration ◽  
Pairwise Correlation ◽  
Bacterial Interactions ◽  
Highly Nonlinear

ABSTRACT There is a growing awareness that bacterial interactions follow a highly nonlinear pattern in reality. However, it is challenging to track the varying bacterial interactions using pairwise correlation analysis, which fails to explore their potential effects on the behavior of microbes. Here, we utilized a regularized sequential locally weighted global linear map (S-map) to capture the varying interspecific interactions from the time series data of a bacterial community under exposure to nitrite. Our results show that bacterial interactions are highly variable and that asymmetric interactions dominate the interaction pattern in a community. Furthermore, we propose a Jacobian coefficient-based statistical method to predict the harmony level of a bacterial community at each successive ecosystem state. The results show that the bacterial community exhibits a higher harmony level in nitrite-treated samples than in the control group. We show that the community harmony level is positively associated with the specific endogenous respiration rates and biofilm formation of the culture. In addition, the community tends to process lower diversity and structural stability under zero- and high-nitrite stresses. We demonstrate that the harmony level, rather than structural stability, is a useful index for unveiling the underlying mechanism of bacterial performance. Overall, the regularized S-map can help us to understand bacterial interactions in ecosystems more accurately than previous approaches. IMPORTANCE It has long been acknowledged that bacterial interactions play important roles in community structure and function. Revealing the interaction variability can allow an understanding of how bacteria respond to perturbation and why bacterial community performance changes. Such information should improve our skills in engineering bacterial communities (e.g., in a wastewater treatment plant) and achieve better removal performance and lower energy consumption.

scholarly journals Bacterial community response to species overrepresentation or omission is strongly influenced by life in spatially structured habitats

2021 ◽  
Author(s):  
Hannah Kleyer ◽  
Robin Tecon ◽  
Dani Or
Keyword(s):  
Bacterial Community ◽  
Species Composition ◽  
Community Composition ◽  
Bacterial Communities ◽  
Liquid Culture ◽  
Interspecific Interactions ◽  
Bacterial Species ◽  
Human Gut ◽  
Natural Habitats ◽  
Bacterial Interactions

AbstractVariations in type and strength of interspecific interactions in natural bacterial communities (e.g., synergistic to inhibitory) affect species composition and community functioning. The extent of interspecific interactions is often modulated by environmental factors that constrain diffusion pathways and cell mobility and limit community spatial arrangement. We studied how spatially structured habitats affect interspecific interactions and influence the resulting bacterial community composition. We used a bacterial community made of 11 well-characterized species that grew in porous habitats (comprised of glass beads) under controlled hydration conditions or in liquid habitats. We manipulated the initial community composition by overrepresenting or removing selected members, and observed community composition over time. Life in porous media reduced the number and strength of interspecific interactions compared to mixed liquid culture, likely due to spatial niche partitioning in porous habitats. The community converged to similar species composition irrespective of the initial species mix, however, the dominant bacterial species was markedly different between liquid culture and structured porous habitats. Moreover, differences in water saturation levels of the porous medium affected community assembly highlighting the need to account for habitat structure and physical conditions to better understand and interpret assembly of bacterial communities. We point at the modulation of bacterial interactions due to spatial structuring as a potential mechanism for promoting community stability and species coexistence, as observed in various natural environments such as soil or human gut.ImportanceBacteria live as complex multispecies communities essential for healthy and functioning ecosystems ranging from soil to the human gut. The bacterial species that form these communities can have positive or negative impact on each other, promoting or inhibiting each other’s growth. Yet, the factors controlling the balance of such interactions in nature, and how these influence the community, are not fully understood. Here, we show that bacterial interactions are modified by life in spatially structured bacterial habitats. These conditions exert important control over the resulting bacterial community regardless of initial species composition. The study demonstrates limitations of inferences from bacterial communities grown in liquid culture relative to behaviour in structured natural habitats such as soil.

scholarly journals Coordination Pattern of the Thigh, Pelvic, and Lumbar Movements during the Gait of Patients with Hip Osteoarthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Takuya Ibara ◽  
Masaya Anan ◽  
Ryosuke Karashima ◽  
Kiyotaka Hada ◽  
Koichi Shinkoda ◽  
...  
Keyword(s):  
Time Series Data ◽  
Hip Osteoarthritis ◽  
Series Data ◽  
Measurement Unit ◽  
Control Group ◽  
Coordination Pattern ◽  
Rotational Movement ◽  
Vector Coding ◽  
Lateral Tilt ◽  
Angular Velocities

There are limited reports on segment movement and their coordination pattern during gait in patients with hip osteoarthritis. To avoid the excessive stress toward the hip and relevant joints, it is important to investigate the coordination pattern between these segment movements, focusing on the time series data. This study aimed to quantify the coordination pattern of lumbar, pelvic, and thigh movements during gait in patients with hip osteoarthritis and in a control group. An inertial measurement unit was used to measure the lumbar, pelvic, and thigh angular velocities during gait of 11 patients with hip osteoarthritis and 11 controls. The vector coding technique was applied, and the coupling angle and the appearance rate of coordination pattern in each direction were calculated and compared with the control group. Compared with the control group, with respect to the lumbar/pelvic segment movements, the patients with hip osteoarthritis spent more rates in anti-phase and lower rates in in-phase lateral tilt movement. With respect to the pelvic/thigh segment movements, the patients with hip osteoarthritis spent more rates within the proximal- and in-phases for lateral tilt movement. Furthermore, patients with osteoarthritis spent lower rates in the distal-phase for anterior/posterior tilt and rotational movement. Patients with hip osteoarthritis could not move their pelvic and thigh segments separately, which indicates the stiffness of the hip joint. The rotational movement and lateral tilt movements, especially, were limited, which is known as Duchenne limp. To maintain the gait ability, it seems important to pay attention to these directional movements.

A Novel Method to Improve the Accuracy of Grey Prediction Model in Economic Prediction

2013 ◽  
Vol 347-350 ◽  
pp. 3331-3335
Author(s):  
Qian Ru Wang ◽  
Xi Wei Chen ◽  
Da Shi Luo ◽  
Yu Feng Wei ◽  
Li Ya Jin ◽  
...  
Keyword(s):  
System Theory ◽  
Time Series Data ◽  
Grey System Theory ◽  
Series Data ◽  
Model Parameters ◽  
Economic Data ◽  
Grey System ◽  
Forecasting Accuracy ◽  
Highly Nonlinear ◽  
The Impact

Grey system theory has been widely used to forecast the economic data that are often highly nonlinear, irregular and non-stationary. Many models based on grey system theory could adapt to various economic time series data. However, some of these models didnt consider the impact of the model parameters, or only considered a simple change of the model parameters for the prediction. In this paper, we proposed the PSO based GM (1, 1) model using the optimized parameters in order to improve the forecasting accuracy. The experiment shows that PSO based GM (1, 1) gets much better forecasting accuracy compared with other widely used grey models on the actual chaotic economic data.

scholarly journals Alterations in Rumen Bacterial Community and Metabolome Characteristics of Cashmere Goats in Response to Dietary Nutrient Density

Animals ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1193
Author(s):  
Yaoyue Wang ◽  
Peng Tang ◽  
Yafei Xiao ◽  
Jianming Liu ◽  
Yulin Chen ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Metabolic Pathways ◽  
High Energy ◽  
High Protein ◽  
Metabolic Energy ◽  
Control Group ◽  
Rrna Gene ◽  
Dietary Energy ◽  
Nutrient Density ◽  
Cashmere Goats

This study was conducted to investigate the impacts of dietary energy and protein on rumen bacterial composition and ruminal metabolites. A total of 12 ruminal samples were collected from Shaanbei white cashmere goats which were divided into two groups, including high-energy and high-protein (Group H; crude protein, CP: 9.37% in dry matter; metabolic energy, ME: 9.24 MJ/kg) and control (Group C; CP: 8.73%; ME: 8.60 MJ/kg) groups. Thereby, 16S rRNA gene sequencing and a quantitative polymerase chain reaction were performed to identify the rumen bacterial community. Metabolomics analysis was done to investigate the rumen metabolites and the related metabolic pathways in Groups C and H. The high-energy and high-protein diets increased the relative abundance of phylum Bacteroidetes and genera Prevotella_1 and Succiniclasticum, while decreasing the number of Proteobacteria (p < 0.05). The dominant differential metabolites were amino acids, peptides, and analogs. Tyrosine metabolism played an important role among the nine main metabolic pathways. Correlation analysis revealed that both Prevotella_1 (r = 0.608, p < 0.05) and Ruminococcus_2 (r = 0.613, p < 0.05) showed a positive correlation with catechol. Our findings revealed that the diets with high energy and protein levels in Group H significantly altered the composition of ruminal bacteria and metabolites, which can help to improve the dietary energy and protein use efficiency in goats.

scholarly journals Effects of Antibiotics on the Bacterial Community, Metabolic Functions and Antibiotic Resistance Genes in Mariculture Sediments during Enrichment Culturing

2020 ◽  
Vol 8 (8) ◽  
pp. 604
Author(s):  
Meng-Qi Ye ◽  
Guan-Jun Chen ◽  
Zong-Jun Du
Keyword(s):  
Antibiotic Resistance ◽  
Bacterial Community ◽  
16S Rrna ◽  
16S Rrna Gene ◽  
High Throughput ◽  
Antibiotic Resistance Genes ◽  
Control Group ◽  
Rrna Gene ◽  
Metabolic Functions ◽  
Culture Dependent

The effect of antibiotics on the diversity and functioning of indigenous microorganisms in the environment has attracted much attention. In this study, effects of exposure to six different antibiotics on the bacterial community, metabolic functions and antibiotic resistance genes (ARGs) in marine sediments during enrichment culturing were investigated. Classical culture-dependent method and high-throughput 16S rRNA gene sequencing method were both applied. In the culture-dependent analysis, the obtained 1549 isolates belonged to four phyla (Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria) and 155 genera. Proteobacteria and Firmicutes were the dominant phyla. The diversity and abundance of obtained bacteria after antibiotic processing exhibited different degrees of decrease. Enrichment culturing for different time could also affect the bacterial community composition. Some genera of bacteria were not isolated in the control group, but they could be isolated in the antibiotic-treated groups. In high-throughput 16S rRNA gene amplicon sequencing analyses, all the effective reads were clustered into 2822 OTUs at 97% similarity cutoff; they were annotated to 49 phyla, 103 class, 220 orders, 347 families, 624 genera and 1122 species. An alpha diversity analysis indicated that the community diversity and richness decreased under antibiotic exposure. The changes at the genus level were much more obvious. Only 48 genera of 129 genera were shared by all the samples. A total of 29 genera which were not detected in the initial control sample could be detected in at least one antibiotic-treated group. SIMPER analysis showed that OTU2543 and OTU1450 were the most common taxa to the dissimilarity of bacterial community between antibiotic-treated groups and the control group. OTU2034 and OUT2543 were the most contributive taxa to dissimilarity of groups incubating for different time. Metabolism was the predominant bacterial function. A total of 30 ARGs were detected in the samples. This study mainly focused on the changes of microbiota under the selective pressure of antibiotics for different time and the results demonstrated that the antibiotic could affect the bacterial diversity and richness in the marine ecosystem.

scholarly journals Effect of Wastewater Treatment Plant Effluent on Microbial Function and Community Structure in the Sediment of a Freshwater Stream with Variable Seasonal Flow

2008 ◽  
Vol 74 (9) ◽  
pp. 2659-2668 ◽  
Author(s):  
Steven A. Wakelin ◽  
Matt J. Colloff ◽  
Rai S. Kookana
Keyword(s):  
Wastewater Treatment ◽  
Community Structure ◽  
Bacterial Community ◽  
16S Rrna ◽  
Wastewater Treatment Plant ◽  
Bacterial Communities ◽  
Nutrient Loading ◽  
Treatment Plant ◽  
Biogeochemical Cycling ◽  
Rrna Genes

ABSTRACT We investigated the effects of wastewater treatment plant (WWTP) discharge on the ecology of bacterial communities in the sediment of a small, low-gradient stream in South Australia. The quantification of genes involved in the biogeochemical cycling of carbon and nitrogen was used to assess potential impacts on ecosystem functions. The effects of disturbance on bacterial community structure were assessed by PCR-denaturing gradient gel electrophoresis of 16S rRNA genes, and clone library analysis was used to phylogenetically characterize significant shifts. Significant (P < 0.05) shifts in bacterial community structures were associated with alteration of the sediment's physicochemical properties, particularly nutrient loading from the WWTP discharge. The effects were greatest at the sampling location 400 m downstream of the outfall where the stream flow is reduced. This highly affected stretch of sediment contained representatives of the gammaproteobacteria that were absent from less-disturbed sites, including Oceanospirillales and Methylococcaceae. 16S rRNA gene sequences from less-disturbed sites had representatives of the Caulobacteraceae, Sphingomonadaceae, and Nitrospirae which were not represented in samples from disturbed sediment. The diversity was lowest at the reference site; it increased with proximity to the WWTP outfall and declined toward highly disturbed (400 m downstream) sites (P < 0.05). The potential for biological transformations of N varied significantly with the stream sediment location (P < 0.05). The abundance of amoA, narG, and nifH genes increased with the distance downstream of the outfall. These processes are driven by N and C availability, as well as redox conditions. Together these data suggest cause and effect between nutrient loading into the creek, shift in bacterial communities through habitat change, and alteration of capacity for biogeochemical cycling of N.

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