scholarly journals Resolving the structure of phage-bacteria interactions in the context of natural diversity

2021 ◽  
Author(s):  
Kathryn M Kauffman ◽  
William K Chang ◽  
Julia M Brown ◽  
Fatima Aysha Hussain ◽  
Joy Y Yang ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Host Range ◽  
Large Scale ◽  
Genomic Diversity ◽  
Interaction Networks ◽  
Bacterial Strains ◽  
Quantitative Estimates ◽  
Phage Evolution ◽  
Marine Vibrio ◽  
In The Wild

Microbial communities are shaped by viral predators. Yet, resolving which viruses (phages) and bacteria are interacting is a major challenge in the context of natural levels of microbial diversity. Thus, fundamental features of how phage-bacteria interactions are structured and evolve in "the wild" remain poorly resolved. Here we use large-scale isolation of environmental marine Vibrio bacteria and their phages to obtain quantitative estimates of strain-level phage predator loads, and use all-by-all host range assays to discover how phage and host genomic diversity shape interactions. We show that killing in environmental interaction networks is sparse - with phage predator loads low for most bacterial strains and phages host-strain-specific in their killing. Paradoxically, we also find that although overlap in killing is generally rare between phages, recombination is common. Together, these results indicate that the number of hosts that phages infect is often larger than the number that they kill and suggest that recombination during cryptic co-infections is an important mode of phage evolution in microbial communities. In the development of phages for bioengineering and therapeutics it will be important to consider that nucleic acids of introduced phages may spread into local phage populations through recombination, and that the likelihood of transfer is not predictable based on killing host range.

scholarly journals Dynamics of infection in a novel group of promiscuous phages and hosts of multiple bacterial genera retrieved from river communities

2020 ◽  
Author(s):  
Daniel Cazares ◽  
Adrian Cazares ◽  
Wendy Figueroa ◽  
Gabriel Guarneros ◽  
Robert A. Edwards ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Host Range ◽  
Production Efficiency ◽  
Sequence Similarity ◽  
Geographic Origin ◽  
Detailed Comparison ◽  
Natural Environments ◽  
Bacterial Strains ◽  
Narrow Host Range ◽  
Natural Systems

AbstractPhages are generally described as species- or even strain-specific viruses, implying an inherent limitation for some to be maintained and spread in diverse bacterial communities. Moreover, phage isolation and host range determination rarely consider the phage ecological context, likely biasing our notion on phage specificity. Here we identified and characterized a novel group of promiscuous phages existing in rivers by using diverse bacteria isolated from the same samples, and then used this biological system to investigate infection dynamics in distantly related hosts. We assembled a diverse collection of over 600 native bacterial strains and used them to isolate six podophages, named Atoyac, from different geographic origin and capable of infecting six genera in the Gammaproteobacteria. Atoyac phage genomes are highly similar to each other but not to those currently available in the genome and metagenome public databases. Detailed comparison of the phage’s infectivity in diverse hosts and trough hundreds of interactions revealed variation in plating efficiency amongst bacterial genera, implying a cost associated with infection of distant hosts, and between phages, despite their sequence similarity. We show, through experimental evolution in single or alternate hosts of different genera, that plaque production efficiency is highly dynamic and tends towards optimization in hosts rendering low plaque formation. Complex adaptation outcomes observed in the evolution experiments differed between highly similar phages and suggest that propagation in multiple hosts may be key to maintain promiscuity in some viruses. Our study expands our knowledge of the virosphere and uncovers bacteria-phage interactions overlooked in natural systems.ImportanceIn natural environments, phages co-exist and interact with a broad variety of bacteria, posing a conundrum for narrow-host-range phages maintenance in diverse communities. This context is rarely considered in the study of host-phage interactions, typically focused on narrow-host-range viruses and their infectivity in target bacteria isolated from sources distinct to where the phages were retrieved from. By studying phage-host interactions in bacteria and viruses isolated from river microbial communities, we show that novel phages with promiscuous host range encompassing multiple bacterial genera can be found in the environment. Assessment of hundreds of interactions in diverse hosts revealed that similar phages exhibit different infection efficiency and adaptation patterns. Understanding host range is fundamental in our knowledge of bacteria-phage interactions and their impact in microbial communities. The dynamic nature of phage promiscuity revealed in our study has implications in different aspects of phage research such as horizontal gene transfer or phage therapy.

scholarly journals First Report of Xanthomonas citri pv. citri-A* Causing Citrus Canker on Lime in Cambodia

Plant Disease ◽  
2008 ◽  
Vol 92 (11) ◽  
pp. 1588-1588 ◽  
Author(s):  
L. Bui Thi Ngoc ◽  
C. Vernière ◽  
O. Pruvost ◽  
T. So ◽  
G. I. Johnson
Keyword(s):  
Host Range ◽  
Large Scale ◽  
Severe Infection ◽  
Citrus Canker ◽  
Aflp Analysis ◽  
Citrus Species ◽  
Bacterial Strains ◽  
Xanthomonas Citri ◽  
Mexican Lime ◽  
Wide Host Range

Asiatic citrus canker caused by Xanthomonas citri pv. citri (X. citri pv. citri-A) is detrimental to citrus production in tropical and subtropical areas. The bacterium can cause severe infection on many citrus species, initially causing water-soaked leaf lesions that become erumpent and necrotic, often with a chlorotic halo. Severe infection causes premature fruit drop and twig dieback. X. citri pv. citri-A has consequently been subject to eradication and international quarantine regulations. In the 1990s, strains with a host range restricted to Mexican lime (Citrus aurantifolia), but not infecting grapefruit (C. paradisi), were described in different areas of Southwest Asia (4). This variant was designated X. citri pv. citri-A* because of its phenotypic and genetic similarities with X. citri pv. citri. Lime leaves with canker lesions were collected in 2007 from a citrus nursery in Kandal Province, Cambodia and isolations were performed with KC semiselective medium (3). Four Xanthomonas-like strains were further characterized by PCR alongside positive control strain CFBP 2525 from New Zealand. The expected DNA fragment was obtained using primer pair 4/7 (2) from the bacterial strains but not when distilled water was used as a template. Amplified fragment length polymorphism (AFLP) analysis of the four X. citri pv. citri strains from Cambodia and reference strains X. citri pv. citri-A (CFBP 2525, CFBP 2900, LMG 9322), -A* (CFBP 2911, JF90-2, JK2-10, JK143-1, JM47-2), and X. citri pv. aurantifolii (CFBP 2866, CFBP 2868, CFBP 2901) using SacI/MspI and four primer pairs (1) separated the Cambodian strains into two distinct haplotypes (i.e., AFLP fingerprint patterns). One haplotype was closely related (evolutionary genome divergences [EGD] ≤0.006 [1]) to X. citri pv. citri-A strains with a wide host range and the other was most genetically related to a strain of X. citri pv. citri-A* from Thailand (EGD of 0.003). On the basis of AFLP, the Cambodian isolates were not related to X. citri pv. aurantifolii (EGD values of >0.060). When inoculated to Mexican lime and Duncan grapefruit using a detached leaf assay in which inoculum droplets containing ∼1 × 106 CFU were deposited on wounds (4), the strains genetically related to X. citri pv. citri-A produced typical canker lesions on both citrus species a week after inoculation, whereas the Cambodian strains related to X. citri pv. citri-A* by AFLP analysis only produced canker lesions on lime. Our finding extended the geographical distribution of pathotype A*. Identification of both pathotypes from a few samples collected in a nursery suggests a potential for large-scale distribution of these strains within the citrus orchards in Cambodia, where the most important citrus crop is sweet orange, suggesting that the occurrence of X. citri pv. citri-A* is of moderate economic significance, in contrast with X. citri pv. citri-A strains with a wide host range. Diseased citrus nursery plants are a major source of primary inoculum in developing countries. Sanitation of citrus nurseries against citrus canker in Cambodia is a prerequisite for improved management of the disease. References: (1) N. Ah-You et al. Phytopathology 97:1568, 2007. (2) J. S. Hartung et al. Phytopathology 86:95, 1996. (3) O. Pruvost et al. J. Appl. Microbiol. 99:803, 2005. (4) C. Vernière et al. Eur. J. Plant Pathol. 104:477, 1998.

Phyto-fabrication of Iron Nanoparticles: Characterization and Antibacterial Capacity

2020 ◽  
Vol 16 ◽  
Author(s):  
Asma S. Algebaly ◽  
Afrah E. Mohammed ◽  
Mudawi M. Elobeid
Keyword(s):  
Electron Microscopy ◽  
Plant Extracts ◽  
Large Scale ◽  
Iron Nanoparticles ◽  
Ethanolic Extract ◽  
Green Technology ◽  
Resistant Bacteria ◽  
Scale Production ◽  
Bacterial Strains ◽  
Plant Sources

Introduction: Fabrication of iron nanoparticles (FeNPs) has recently gained a great concern for their varied applications in remediation technologies of the environment. Objective: The current study aimed to fabricate iron nanoparticles by green technology approach using different plant sources, Azadirachta indica leaf and Calligonum comosum root following two extraction methods. Methods: Currently, a mixture of FeCl2 and FeCl3 was used to react with the plant extracts which are considered as reducing and stabilizing agents for the generation of FeNPs in one step. Different techniques were used for FeNPs identification. Results: Immediately after mixing of the two reaction components, the color changed to dark brown as an indication of safe conversion of Fe ions to FeNPs, that later confirmed by zeta sizer, transmission electron microscopy (TEM) and scanning electron microscopy (SEM). FeNPs fabricated by C. comosum showed smaller size when compared by those fabricated by A. indica. Using both plant sources, FeNPs fabricated by the aqueous extract had smaller size in relation to those fabricated by ethanolic extract. Furthermore, antibacterial ability against two bacterial strains was approved. Conclusion: The current results indicated that, at room temperature plant extracts fabricated Fe ion to Fe nanoparticles, suggesting its probable usage for large scale production as well as its suitability against bacteria. It could also be recommended for antibiotic resistant bacteria.

scholarly journals Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation

2021 ◽  
Author(s):  
Mehdi Bahri ◽  
Eimear O’ Sullivan ◽  
Shunwang Gong ◽  
Feng Liu ◽  
Xiaoming Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Training Time ◽  
3D Face ◽  
In The Wild ◽  
Previous State ◽  
Surface Translation ◽  
Visual Attention Mechanism ◽  
Diverse Data ◽  
Human Faces ◽  
Robust To Noise

AbstractStandard registration algorithms need to be independently applied to each surface to register, following careful pre-processing and hand-tuning. Recently, learning-based approaches have emerged that reduce the registration of new scans to running inference with a previously-trained model. The potential benefits are multifold: inference is typically orders of magnitude faster than solving a new instance of a difficult optimization problem, deep learning models can be made robust to noise and corruption, and the trained model may be re-used for other tasks, e.g. through transfer learning. In this paper, we cast the registration task as a surface-to-surface translation problem, and design a model to reliably capture the latent geometric information directly from raw 3D face scans. We introduce Shape-My-Face (SMF), a powerful encoder-decoder architecture based on an improved point cloud encoder, a novel visual attention mechanism, graph convolutional decoders with skip connections, and a specialized mouth model that we smoothly integrate with the mesh convolutions. Compared to the previous state-of-the-art learning algorithms for non-rigid registration of face scans, SMF only requires the raw data to be rigidly aligned (with scaling) with a pre-defined face template. Additionally, our model provides topologically-sound meshes with minimal supervision, offers faster training time, has orders of magnitude fewer trainable parameters, is more robust to noise, and can generalize to previously unseen datasets. We extensively evaluate the quality of our registrations on diverse data. We demonstrate the robustness and generalizability of our model with in-the-wild face scans across different modalities, sensor types, and resolutions. Finally, we show that, by learning to register scans, SMF produces a hybrid linear and non-linear morphable model. Manipulation of the latent space of SMF allows for shape generation, and morphing applications such as expression transfer in-the-wild. We train SMF on a dataset of human faces comprising 9 large-scale databases on commodity hardware.

scholarly journals Phenotypically and Genotypically Heterogeneous Strains of Pseudomonas syringae Associated With Alfalfa Leaf Spot Disease in Iran

Plant Disease ◽  
2019 ◽  
Vol 103 (12) ◽  
pp. 3199-3208 ◽  
Author(s):  
Maryam Ansari ◽  
S. Mohsen Taghavi ◽  
Sadegh Zarei ◽  
Soraya Mehrb-Moghadam ◽  
Hamzeh Mafakheri ◽  
...  
Keyword(s):  
Host Range ◽  
Pseudomonas Syringae ◽  
Leaf Spot ◽  
Phylogenetic Analyses ◽  
Housekeeping Genes ◽  
Pcr Primers ◽  
Phylogenetic Position ◽  
Leaf Spot Disease ◽  
Bacterial Strains ◽  
Alfalfa Leaf

In this study, we provide a polyphasic characterization of 18 Pseudomonas spp. strains associated with alfalfa leaf spot symptoms in Iran. All of the strains were pathogenic on alfalfa, although the aggressiveness and symptomology varied among the strains. All strains but one were pathogenic on broad bean, cucumber, honeydew, and zucchini, whereas only a fraction of the strains were pathogenic on sugar beet, tomato, and wheat. Syringomycin biosynthesis genes (syrB1 and syrP) were detected using the corresponding PCR primers in all of the strains isolated from alfalfa. Phylogenetic analyses using the sequences of four housekeeping genes (gapA, gltA, gyrB, and rpoD) revealed that all of the strains except one (Als34) belong to phylogroup 2b of P. syringae sensu lato, whereas strain Als34 placed within phylogroup 1 close to the type strain of P. syringae pv. apii. Among the phylogroup 2b strains, nine strains were phylogenetically close to the P. syringae pv. aptata clade, whereas the remainder were scattered among P. syringae pv. atrofaciens and P. syringae pv. syringae strains. Pathogenicity and host range assays of the bacterial strains evaluated in this study on a set of taxonomically diverse plant species did not allow us to assign a “pathovar” status to the alfalfa strains. However, these results provide novel insight into the host range and phylogenetic position of the alfalfa-pathogenic members of P. syringae sensu lato, and they reveal that phenotypically and genotypically heterogeneous strains of the pathogen cause bacterial leaf spot of alfalfa.

Screening and Isolation of Bacterial Strains with the Biotechnological Potential to Destruct Cyanide-Bearing Compounds under the Conditions of Extreme Continental Climate

2015 ◽  
Vol 1130 ◽  
pp. 19-22
Author(s):  
M.P. Belykh ◽  
S.V. Petrov ◽  
V.F. Petrov ◽  
A.Yu. Chikin ◽  
N.L. Belkova
Keyword(s):  
Microbial Communities ◽  
Gold Mining ◽  
Molecular Genetic ◽  
Heap Leaching ◽  
Bacterial Strains ◽  
Mining Operations ◽  
Biotechnological Potential ◽  
Enriched Cultures ◽  
Continental Climate

The methods of biodegradation are of special interest because they help solving environmental problems of wastes detoxification from gold-mining operations. The use of bacterial strains is a promising approach in the field of biotechnology to destruct cyanide-bearing compounds. The diversity of microbial communities both in heap in situ and in the enriched cultures was studied with molecular genetic methods. The differences in representation of bacteria, cultivated in unexploitable and operating heaps, are territory, site and heap specific. The strains of Pseudomonas sp. and Methylobacterium sp. possess the biotechnological potential and might be used in biodegradation of heap leaching wastes in extreme continental climate.

scholarly journals TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

2018 ◽  
pp. 310-327 ◽  
Author(s):  
Matthias Müller ◽  
Adel Bibi ◽  
Silvio Giancola ◽  
Salman Alsubaihi ◽  
Bernard Ghanem
Keyword(s):  
Object Tracking ◽  
Large Scale ◽  
Large Scale Dataset ◽  
In The Wild

scholarly journals Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Pengshuo Yang ◽  
Chongyang Tan ◽  
Maozhen Han ◽  
Lin Cheng ◽  
Xuefeng Cui ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Large Scale ◽  
Network Connectivity ◽  
Small Range ◽  
Environmental Disturbance ◽  
Target Species ◽  
Important Species ◽  
Metagenome Analysis ◽  
Occurrence Patterns ◽  
Edge Networks

Abstract Mainstream studies of microbial community focused on critical organisms and their physiology. Recent advances in large-scale metagenome analysis projects initiated new researches in the complex correlations between large microbial communities. Specifically, previous studies focused on the nodes (i.e. species) of the Species-Centric Networks (SCNs). However, little was understood about the change of correlation between network members (i.e. edges of the SCNs) when the network was disturbed. Here, we introduced a Correlation-Centric Network (CCN) to the microbial research based on the concept of edge networks. In CCN, each node represented a species–species correlation, and edge represented the species shared by two correlations. In this research, we investigated the CCNs and their corresponding SCNs on two large cohorts of microbiome. The results showed that CCNs not only retained the characteristics of SCNs, but also contained information that cannot be detected by SCNs. In addition, when the members of microbial communities were decreased (i.e. environmental disturbance), the CCNs fluctuated within a small range in terms of network connectivity. Therefore, by highlighting the important species correlations, CCNs could unveil new insights when studying not only the functions of target species, but also the stabilities of their residing microbial communities.

scholarly journals Deciphering the evolution of microbial interactions: in silico studies of two-member microbial communities

2022 ◽  
Author(s):  
Gayathri Sambamoorthy ◽  
Karthik Raman
Keyword(s):  
Microbial Communities ◽  
In Silico ◽  
Microbial Interactions ◽  
Interaction Patterns ◽  
Wild Type ◽  
Community Function ◽  
Evolutionary Forces ◽  
In Silico Studies ◽  
Wide Range ◽  
In The Wild

Microbes thrive in communities, embedded in a complex web of interactions. These interactions, particularly metabolic interactions, play a crucial role in maintaining the community structure and function. As the organisms thrive and evolve, a variety of evolutionary processes alter the interactions among the organisms in the community, although the community function remains intact. In this work, we simulate the evolution of two-member microbial communities in silico to study how evolutionary forces can shape the interactions between organisms. We employ genomescale metabolic models of organisms from the human gut, which exhibit a range of interaction patterns, from mutualism to parasitism. We observe that the evolution of microbial interactions varies depending upon the starting interaction and also on the metabolic capabilities of the organisms in the community. We find that evolutionary constraints play a significant role in shaping the dependencies of organisms in the community. Evolution of microbial communities yields fitness benefits in only a small fraction of the communities, and is also dependent on the interaction type of the wild-type communities. The metabolites cross-fed in the wild-type communities appear in only less than 50% of the evolved communities. A wide range of new metabolites are cross-fed as the communities evolve. Further, the dynamics of microbial interactions are not specific to the interaction of the wild-type community but vary depending on the organisms present in the community. Our approach of evolving microbial communities in silico provides an exciting glimpse of the dynamics of microbial interactions and offers several avenues for future investigations.

scholarly journals deepNF: Deep network fusion for protein function prediction

2017 ◽  
Author(s):  
Vladimir Gligorijević ◽  
Meet Barot ◽  
Richard Bonneau
Keyword(s):  
Protein Function ◽  
Large Scale ◽  
Protein Function Prediction ◽  
Predictive Performance ◽  
Substantial Improvement ◽  
Function Prediction ◽  
Interaction Networks ◽  
Highly Nonlinear ◽  
High Level ◽  
String Networks

AbstractThe prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provide a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that cannot capture complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity.AvailabilitydeepNF is freely available at: https://github.com/VGligorijevic/deepNF

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