Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 5 de 5
Filtrar
Mais filtros











Base de dados
Intervalo de ano de publicação
1.
Proc Natl Acad Sci U S A ; 121(6): e2300644120, 2024 Feb 06.
Artigo em Inglês | MEDLINE | ID: mdl-38306481

RESUMO

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin's role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.


Assuntos
COVID-19 , SARS-CoV-2 , Humanos , Animais , Camundongos , Células Endoteliais , Proteoma , Peptídeos
2.
Curr Opin Struct Biol ; 75: 102435, 2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-35863164

RESUMO

Bacteria are microscopic, single-celled organisms known for their ability to adapt to their environment. In response to stressful environmental conditions or in the presence of a contact surface, they commonly form multicellular aggregates called biofilms. Biofilms form on various abiotic or biotic surfaces through a dynamic stepwise process involving adhesion, growth, and extracellular matrix production. Biofilms develop on tissues as well as on implanted devices during infections, providing the bacteria with a mechanism for survival under harsh conditions including targeting by the immune system and antimicrobial therapy. Like pathogenic bacteria, members of the human microbiota can form biofilms. Biofilms formed by enteric bacteria contribute to several human diseases including autoimmune diseases and cancer. However, until recently the interactions of immune cells with biofilms had been mostly uncharacterized. Here, we will discuss how components of the enteric biofilm produced in vivo, specifically amyloid curli and extracellular DNA, could be interacting with the host's immune system causing an unpredicted immune response.


Assuntos
Doenças Autoimunes , Autoimunidade , Amiloide , Proteínas Amiloidogênicas , Bactérias , Biofilmes , Humanos
3.
Front Immunol ; 11: 1873, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33013838

RESUMO

Antimicrobial compounds first arose in prokaryotes by necessity for competitive self-defense. In this light, prokaryotes invented the first host defense peptides. Among the most well-characterized of these peptides are class II bacteriocins, ribosomally-synthesized polypeptides produced chiefly by Gram-positive bacteria. In the current study, a tensor search protocol-the BACIIα algorithm-was created to identify and classify bacteriocin sequences with high fidelity. The BACIIα algorithm integrates a consensus signature sequence, physicochemical and genomic pattern elements within a high-dimensional query tool to select for bacteriocin-like peptides. It accurately retrieved and distinguished virtually all families of known class II bacteriocins, with an 86% specificity. Further, the algorithm retrieved a large set of unforeseen, putative bacteriocin peptide sequences. A recently-developed machine-learning classifier predicted the vast majority of retrieved sequences to induce negative Gaussian curvature in target membranes, a hallmark of antimicrobial activity. Prototypic bacteriocin candidate sequences were synthesized and demonstrated potent antimicrobial efficacy in vitro against a broad spectrum of human pathogens. Therefore, the BACIIα algorithm expands the scope of prokaryotic host defense bacteriocins and enables an innovative bioinformatics discovery strategy. Understanding how prokaryotes have protected themselves against microbial threats over eons of time holds promise to discover novel anti-infective strategies to meet the challenge of modern antibiotic resistance.


Assuntos
Bacteriocinas , Biologia Computacional/métodos , Aprendizado de Máquina , Bacteriocinas/química , Bacteriocinas/classificação , Bacteriocinas/genética
4.
mBio ; 11(1)2020 02 25.
Artigo em Inglês | MEDLINE | ID: mdl-32098815

RESUMO

What are bacteria doing during "reversible attachment," the period of transient surface attachment when they initially engage a surface, besides attaching themselves to the surface? Can an attaching cell help any other cell attach? If so, does it help all cells or employ a more selective strategy to help either nearby cells (spatial neighbors) or its progeny (temporal neighbors)? Using community tracking methods at the single-cell resolution, we suggest answers to these questions based on how reversible attachment progresses during surface sensing for Pseudomonas aeruginosa strains PAO1 and PA14. Although PAO1 and PA14 exhibit similar trends of surface cell population increase, they show unanticipated differences when cells are considered at the lineage level and interpreted using the quantitative framework of an exactly solvable stochastic model. Reversible attachment comprises two regimes of behavior, processive and nonprocessive, corresponding to whether cells of the lineage stay on the surface long enough to divide, or not, before detaching. Stark differences between PAO1 and PA14 in the processive regime of reversible attachment suggest the existence of two surface colonization strategies. PAO1 lineages commit quickly to a surface compared to PA14 lineages, with early c-di-GMP-mediated exopolysaccharide (EPS) production that can facilitate the attachment of neighbors. PA14 lineages modulate their motility via cyclic AMP (cAMP) and retain memory of the surface so that their progeny are primed for improved subsequent surface attachment. Based on the findings of previous studies, we propose that the differences between PAO1 and PA14 are potentially rooted in downstream differences between Wsp-based and Pil-Chp-based surface-sensing systems, respectively.IMPORTANCE The initial pivotal phase of bacterial biofilm formation known as reversible attachment, where cells undergo a period of transient surface attachment, is at once universal and poorly understood. What is more, although we know that reversible attachment culminates ultimately in irreversible attachment, it is not clear how reversible attachment progresses phenotypically, as bacterial surface-sensing circuits fundamentally alter cellular behavior. We analyze diverse observed bacterial behavior one family at a time (defined as a full lineage of cells related to one another by division) using a unifying stochastic model and show that our findings lead to insights on the time evolution of reversible attachment and the social cooperative dimension of surface attachment in PAO1 and PA14 strains.


Assuntos
Bactérias/metabolismo , Biofilmes/crescimento & desenvolvimento , Pseudomonas aeruginosa/fisiologia , Aderência Bacteriana , Fenômenos Fisiológicos Bacterianos , Proteínas de Bactérias , AMP Cíclico/metabolismo , Modelos Teóricos
5.
Proc Natl Acad Sci U S A ; 115(17): 4471-4476, 2018 04 24.
Artigo em Inglês | MEDLINE | ID: mdl-29559526

RESUMO

Using multigenerational, single-cell tracking we explore the earliest events of biofilm formation by Pseudomonas aeruginosa During initial stages of surface engagement (≤20 h), the surface cell population of this microbe comprises overwhelmingly cells that attach poorly (∼95% stay <30 s, well below the ∼1-h division time) with little increase in surface population. If we harvest cells previously exposed to a surface and direct them to a virgin surface, we find that these surface-exposed cells and their descendants attach strongly and then rapidly increase the surface cell population. This "adaptive," time-delayed adhesion requires determinants we showed previously are critical for surface sensing: type IV pili (TFP) and cAMP signaling via the Pil-Chp-TFP system. We show that these surface-adapted cells exhibit damped, coupled out-of-phase oscillations of intracellular cAMP levels and associated TFP activity that persist for multiple generations, whereas surface-naïve cells show uncorrelated cAMP and TFP activity. These correlated cAMP-TFP oscillations, which effectively impart intergenerational memory to cells in a lineage, can be understood in terms of a Turing stochastic model based on the Pil-Chp-TFP framework. Importantly, these cAMP-TFP oscillations create a state characterized by a suppression of TFP motility coordinated across entire lineages and lead to a drastic increase in the number of surface-associated cells with near-zero translational motion. The appearance of this surface-adapted state, which can serve to define the historical classification of "irreversibly attached" cells, correlates with family tree architectures that facilitate exponential increases in surface cell populations necessary for biofilm formation.


Assuntos
Aderência Bacteriana/fisiologia , Biofilmes/crescimento & desenvolvimento , AMP Cíclico/metabolismo , Fímbrias Bacterianas/fisiologia , Pseudomonas aeruginosa/fisiologia , Sistemas do Segundo Mensageiro/fisiologia
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA