scholarly journals Utilizing Whole Fusobacterium Genomes To Identify, Correct, and Characterize Potential Virulence Protein Families

2019 ◽  
Vol 201 (23) ◽  
Author(s):  
Ariana Umaña ◽  
Blake E. Sanders ◽  
Christopher C. Yoo ◽  
Michael A. Casasanta ◽  
Barath Udayasuryan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Virulence Factors ◽  
Serine Proteases ◽  
Sequence Similarity ◽  
Protein Families ◽  
Emerging Pathogens ◽  
Content Type ◽  
Virulence Protein ◽  
Similarity Networks ◽  
Sequence Similarity Networks

ABSTRACT Fusobacterium spp. are Gram-negative, anaerobic, opportunistic pathogens involved in multiple diseases, including a link between the oral pathogen Fusobacterium nucleatum and the progression and severity of colorectal cancer. The identification and characterization of virulence factors in the genus Fusobacterium has been greatly hindered by a lack of properly assembled and annotated genomes. Using newly completed genomes from nine strains and seven species of Fusobacterium, we report the identification and corrected annotation of verified and potential virulence factors from the type 5 secreted autotransporter, FadA, and MORN2 protein families, with a focus on the genetically tractable strain F. nucleatum subsp. nucleatum ATCC 23726 and type strain F. nucleatum subsp. nucleatum ATCC 25586. Within the autotransporters, we used sequence similarity networks to identify protein subsets and show a clear differentiation between the prediction of outer membrane adhesins, serine proteases, and proteins with unknown function. These data have identified unique subsets of type 5a autotransporters, which are key proteins associated with virulence in F. nucleatum. However, we coupled our bioinformatic data with bacterial binding assays to show that a predicted weakly invasive strain of F. necrophorum that lacks a Fap2 autotransporter adhesin strongly binds human colonocytes. These analyses confirm a gap in our understanding of how autotransporters, MORN2 domain proteins, and FadA adhesins contribute to host interactions and invasion. In summary, we identify candidate virulence genes in Fusobacterium, and caution that experimental validation of host-microbe interactions should complement bioinformatic predictions to increase our understanding of virulence protein contributions in Fusobacterium infections and disease. IMPORTANCE Fusobacterium spp. are emerging pathogens that contribute to mammalian and human diseases, including colorectal cancer. Despite a validated connection with disease, few proteins have been characterized that define a direct molecular mechanism for Fusobacterium pathogenesis. We report a comprehensive examination of virulence-associated protein families in multiple Fusobacterium species and show that complete genomes facilitate the correction and identification of multiple, large type 5a secreted autotransporter genes in previously misannotated or fragmented genomes. In addition, we use protein sequence similarity networks and human cell interaction experiments to show that previously predicted noninvasive strains can indeed bind to and potentially invade human cells and that this could be due to the expansion of specific virulence proteins that drive Fusobacterium infections and disease.

scholarly journals Reevaluating the Fusobacterium Virulence Factor Landscape

2019 ◽  
Author(s):  
Ariana Umana ◽  
Blake E. Sanders ◽  
Chris C. Yoo ◽  
Michael A. Casasanta ◽  
Barath Udayasuryan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Virulence Factors ◽  
Protein Sequence ◽  
Sequence Similarity ◽  
Human Cells ◽  
Protein Families ◽  
Diverse Range ◽  
Similarity Networks ◽  
Protein Sequence Similarity ◽  
Sequence Similarity Networks

ABSTRACTFusobacteríum are Gram-negative, anaerobic, opportunistic pathogens involved in multiple diseases, including the oral pathogen Fusobacterium nucleatum being linked to the progression and severity of colorectal cancer. The global identification of virulence factors in Fusobacterium has been greatly hindered by a lack of properly assembled and annotated genomes. Using newly completed genomes from nine strains and seven species of Fusobacterium, we report the identification and correction of virulence factors from the Type 5 secreted autotransporter and FadA protein families, with a focus on the genetically tractable strain F. nucleatum subsp. nucleatum ATCC 23726 and the classic typed strain F. nucleatum subsp. nucleatum ATCC 25586. Within the autotransporters, we employed protein sequence similarity networks to identify subsets of virulence factors, and show a clear differentiation between the prediction of outer membrane adhesins, serine proteases, and proteins with unknown function. These data have defined protein subsets within the Type 5a effectors that are present in predicted invasive strains but are broadly lacking in passively invading strains; a key phenotype associated with Fusobacterium virulence. However, our data shows that prior bioinformatic analysis that predicted species of Fusobacterium to be non-¡nvasive can indeed invade human cells, and that pure phylogenetic analysis to determine the virulence within this bacterial genus should be used cautiously and subsequently paired with experiments to validate these hypotheses. In addition, we provide data that show a complex interplay between autotransporters, MORN2 domain containing proteins, and FadA adhesins that we hypothesize synergistically contribute to host cell interactions and invasion. In summary, we report that accurate open reading frame annotations using complete Fusobacterium genomes, in combination with experimental validation of invasion, redefines the repertoire of virulence factors that could be contributing to the species specific pathology of multiple Fusobacterium induced infections and diseases.IMPORTANCEFusobacterium are emerging pathogens that contribute to the progression and severity of multiple mammalian and human infectious diseases, including colorectal cancer. Despite a validated connection with disease, a limited number of proteins have been characterized that define a direct molecular mechanism for pathogenesis in a diverse range of host tissue infections. We report a comprehensive examination of virulence associated protein families in multiple Fusobacterium species, and show that complete genomes facilitate the correction and identification of multiple, large Type 5a secreted autotransporter genes in previously misannotated or fragmented genomes. In addition, we use protein sequence similarity networks and human cell invasion experiments to show that previously predicted non-invasive strains can indeed enter human cells, and that this is likely due to the expansion of specific virulence proteins that drive F. nucleatum infections and disease.

scholarly journals Diversity of GPI-anchored fungal adhesins

2020 ◽  
Vol 401 (12) ◽  
pp. 1389-1405
Author(s):  
Lars-Oliver Essen ◽  
Marian Samuel Vogt ◽  
Hans-Ulrich Mösch
Keyword(s):  
Cell Wall ◽  
Cell Surface ◽  
Bioinformatics Analysis ◽  
Current Knowledge ◽  
Sequence Similarity ◽  
Growth Forms ◽  
Similarity Networks ◽  
Fungal Adhesins ◽  
Sequence Similarity Networks ◽  
Successful Colonization

AbstractSelective adhesion of fungal cells to one another and to foreign surfaces is fundamental for the development of multicellular growth forms and the successful colonization of substrates and host organisms. Accordingly, fungi possess diverse cell wall-associated adhesins, mostly large glycoproteins, which present N-terminal adhesion domains at the cell surface for ligand recognition and binding. In order to function as robust adhesins, these glycoproteins must be covalently linkedto the cell wall via C-terminal glycosylphosphatidylinositol (GPI) anchors by transglycosylation. In this review, we summarize the current knowledge on the structural and functional diversity of so far characterized protein families of adhesion domains and set it into a broad context by an in-depth bioinformatics analysis using sequence similarity networks. In addition, we discuss possible mechanisms for the membrane-to-cell wall transfer of fungal adhesins by membrane-anchored Dfg5 transglycosidases.

scholarly journals Community detection in sequence similarity networks based on attribute clustering

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0178650
Author(s):  
Janamejaya Chowdhary ◽  
Frank E. Löffler ◽  
Jeremy C. Smith
Keyword(s):  
Community Detection ◽  
Sequence Similarity ◽  
Similarity Networks ◽  
Sequence Similarity Networks ◽  
Attribute Clustering

scholarly journals Sequence Similarity Networks for the Protein Universe

2015 ◽  
Vol 29 (S1) ◽  
Author(s):  
Katie Whalen ◽  
Boris Sadkhin ◽  
Daniel Davidson ◽  
John Gerlt
Keyword(s):  
Sequence Similarity ◽  
Protein Universe ◽  
Similarity Networks ◽  
Sequence Similarity Networks

Transfer index, NetUniFrac and some useful shortest path-based distances for community analysis in sequence similarity networks

2020 ◽  
Vol 36 (9) ◽  
pp. 2740-2749
Author(s):  
Henry Xing ◽  
Steven W Kembel ◽  
Vladimir Makarenkov
Keyword(s):  
Gene Transfer ◽  
Horizontal Gene Transfer ◽  
Phylogenetic Tree ◽  
Shortest Path ◽  
Sequence Similarity ◽  
Community Analysis ◽  
Supplementary Information ◽  
Similarity Networks ◽  
Transfer Index ◽  
Sequence Similarity Networks

Abstract Motivation Phylogenetic trees and the methods for their analysis have played a key role in many evolutionary, ecological and bioinformatics studies. Alternatively, phylogenetic networks have been widely used to analyze and represent complex reticulate evolutionary processes which cannot be adequately studied using traditional phylogenetic methods. These processes include, among others, hybridization, horizontal gene transfer, and genetic recombination. Nowadays, sequence similarity and genome similarity networks have become an efficient tool for community analysis of large molecular datasets in comparative studies. These networks can be used for tackling a variety of complex evolutionary problems such as the identification of horizontal gene transfer events, the recovery of mosaic genes and genomes, and the study of holobionts. Results The shortest path in a phylogenetic tree is used to estimate evolutionary distances between species. We show how the shortest path concept can be extended to sequence similarity networks by defining five new distances, NetUniFrac, Spp, Spep, Spelp and Spinp, and the Transfer index, between species communities present in the network. These new distances can be seen as network analogs of the traditional UniFrac distance used to assess dissimilarity between species communities in a phylogenetic tree, whereas the Transfer index is intended for estimating the rate and direction of gene transfers, or species dispersal, between different phylogenetic, or ecological, species communities. Moreover, NetUniFrac and the Transfer index can be computed in linear time with respect to the number of edges in the network. We show how these new measures can be used to analyze microbiota and antibiotic resistance gene similarity networks. Availability and implementation Our NetFrac program, implemented in R and C, along with its source code, is freely available on Github at the following URL address: https://github.com/XPHenry/Netfrac. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The Spl Serine Proteases Modulate Staphylococcus aureus Protein Production and Virulence in a Rabbit Model of Pneumonia

mSphere ◽  
2016 ◽  
Vol 1 (5) ◽  
Author(s):  
Alexandra E. Paharik ◽  
Wilmara Salgado-Pabon ◽  
David K. Meyerholz ◽  
Mark J. White ◽  
Patrick M. Schlievert ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Virulence Factors ◽  
Serine Proteases ◽  
Rabbit Model ◽  
Human Infection ◽  
Lung Damage ◽  
Wild Type ◽  
Content Type ◽  
Associated Proteins ◽  
Human Proteins

ABSTRACT Staphylococcus aureus is a versatile human pathogen that produces an array of virulence factors, including several proteases. Of these, six proteases called the Spls are the least characterized. Previous evidence suggests that the Spls are expressed during human infection; however, their function is unknown. Our study shows that the Spls are required for S. aureus to cause disseminated lung damage during pneumonia. Further, we present the first example of a human protein cut by an Spl protease. Although the Spls were predicted not to cut staphylococcal proteins, we also show that an spl mutant has altered abundance of both secreted and surface-associated proteins. This work provides novel insight into the function of Spls during infection and their potential ability to degrade both staphylococcal and human proteins. The Spl proteases are a group of six serine proteases that are encoded on the νSaβ pathogenicity island and are unique to Staphylococcus aureus. Despite their interesting biochemistry, their biological substrates and functions in virulence have been difficult to elucidate. We found that an spl operon mutant of the community-associated methicillin-resistant S. aureus USA300 strain LAC induced localized lung damage in a rabbit model of pneumonia, characterized by bronchopneumonia observed histologically. Disease in the mutant-infected rabbits was restricted in distribution compared to that in wild-type USA300-infected rabbits. We also found that SplA is able to cleave the mucin 16 glycoprotein from the surface of the CalU-3 lung cell line, suggesting a possible mechanism for wild-type USA300 spreading pneumonia to both lungs. Investigation of the secreted and surface proteomes of wild-type USA300 and the spl mutant revealed multiple alterations in metabolic proteins and virulence factors. This study demonstrates that the Spls modulate S. aureus physiology and virulence, identifies a human target of SplA, and suggests potential S. aureus targets of the Spl proteases. IMPORTANCE Staphylococcus aureus is a versatile human pathogen that produces an array of virulence factors, including several proteases. Of these, six proteases called the Spls are the least characterized. Previous evidence suggests that the Spls are expressed during human infection; however, their function is unknown. Our study shows that the Spls are required for S. aureus to cause disseminated lung damage during pneumonia. Further, we present the first example of a human protein cut by an Spl protease. Although the Spls were predicted not to cut staphylococcal proteins, we also show that an spl mutant has altered abundance of both secreted and surface-associated proteins. This work provides novel insight into the function of Spls during infection and their potential ability to degrade both staphylococcal and human proteins.

scholarly journals Motif Analysis in k-mer Networks: An Approach towards Understanding SARS-CoV-2 Geographical Shifts

2020 ◽  
Author(s):  
Sourav Biswas ◽  
Suparna Saha ◽  
Sanghamitra Bandyopadhyay ◽  
Malay Bhattacharyya
Keyword(s):  
Geographical Origin ◽  
Sequence Similarity ◽  
Motif Analysis ◽  
Significant Difference ◽  
The Usa ◽  
Under Sampling ◽  
Similarity Networks ◽  
Sequence Similarity Networks ◽  
Frequency Counts ◽  
Day By Day

AbstractWith an increasing number of SARS-CoV-2 sequences available day by day, new genomic information is getting revealed to us. As SARS-CoV-2 sequences highlight wide changes across the samples, we aim to explore whether these changes reveal the geographical origin of the corresponding samples. The k-mer distributions, denoting normalized frequency counts of all possible combinations of nucleotide of size upto k, are often helpful to explore sequence level patterns. Given the SARS-CoV-2 sequences are highly imbalanced by its geographical origin (relatively with a higher number samples collected from the USA), we observe that with proper under-sampling k-mer distributions in the SARS-CoV-2 sequences predict its geographical origin with more than 90% accuracy. The experiments are performed on the samples collected from six countries with maximum number of sequences available till July 07, 2020. This comprises SARS-CoV-2 sequences from Australia, USA, China, India, Greece and France. Moreover, we demonstrate that the changes of genomic sequences characterize the continents as a whole. We also highlight that the network motifs present in the sequence similarity networks have a significant difference across the said countries. This, as a whole, is capable of predicting the geographical shift of SARS-CoV-2.

scholarly journals Eukaryote Genes Are More Likely than Prokaryote Genes to Be Composites

Genes ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 648
Author(s):  
Yaqing Ou ◽  
James O. McInerney
Keyword(s):  
Sequence Similarity ◽  
Evolutionary Process ◽  
Mobile Genetic Elements ◽  
Functional Categories ◽  
Genetic Elements ◽  
New Genes ◽  
Domains Of Life ◽  
Similarity Networks ◽  
Partial Homology ◽  
Sequence Similarity Networks

The formation of new genes by combining parts of existing genes is an important evolutionary process. Remodelled genes, which we call composites, have been investigated in many species, however, their distribution across all of life is still unknown. We set out to examine the extent to which genomes from cells and mobile genetic elements contain composite genes. We identify composite genes as those that show partial homology to at least two unrelated component genes. In order to identify composite and component genes, we constructed sequence similarity networks (SSNs) of more than one million genes from all three domains of life, as well as viruses and plasmids. We identified non-transitive triplets of nodes in this network and explored the homology relationships in these triplets to see if the middle nodes were indeed composite genes. In total, we identified 221,043 (18.57%) composites genes, which were distributed across all genomic and functional categories. In particular, the presence of composite genes is statistically more likely in eukaryotes than prokaryotes.

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