Creating microbiome-model harmony between metaproteomics data and the ADM1da for a two-step anaerobic digester DOI Creative Commons
Patrick Hellwig,

Ingolf Seick,

Nicole Meinusch

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 22, 2024

Abstract The effective operation, planning, and optimization of renewable energy production in anaerobic digestion (AD) plants relies on advanced process models, such as the Anaerobic Digestion Model No. 1 (ADM1). This study applies an ADM1-based model (ADM1da) to simulate a two-step digester industrial setting. data demonstrate that 2.6% methane is lost result open hydrolysis. Conversely, incorporation hydrolysis fermenter enhances by average 2.5%. Although ADM1-like models are widely recognized for accurately representing processes, mechanistic insights into microbiome involved have been limited absence tools analyze microbial composition functionality at time these were developed. To overcome this limitation, we utilized metaproteomics approach assess abundance biomass-correlated activity groups defined model, aiming bridge gap between ecology bioprocess engineering AD systems. We also developed evaluated series rules associating particular species with functional model. Our analysis demonstrates while supports presence stable main fermenter, it difficult capture dynamic behavior observed fermenter. Furthermore, actual displays greater versatility than assumes, microorganisms performing multiple functions rather being restricted single roles. In conclusion, identifies options improving integrating comprehensive biological knowledge further optimize performance digesters. Highlights Simulations revealed 2.6 % volume loss attributed Implementation increased 2.5% Identification map ADM1da depict but not Microbial perform just one assumed

Язык: Английский

Dysbiosis of Oral Microbiome: A Key Player in Oral Carcinogenesis? A Critical Review DOI Creative Commons
K. Devaraja, Sadhna Aggarwal

Biomedicines, Год журнала: 2025, Номер 13(2), С. 448 - 448

Опубликована: Фев. 12, 2025

The oral cavity is known to harbor hundreds of microorganisms, belonging various genera, constituting a peculiar flora called the microbiome. change in relative distribution constituents this microbial flora, due any reason, leads dysbiosis. For centuries, dysbiosis has been linked etiopathogenesis several medical illnesses, both locally and systemically-. However, aided by recent advent bio-technological capabilities, reports have re-emerged that link carcinogenesis, numerous studies are currently exploring their association plausible mechanisms. Some proposed mechanisms dysbiosis-induced carcinogenesis (ODIC) include—a bacteria-induced chronic inflammatory state leading direct cellular damage, inflammatory-cytokine-mediated promotion proliferation invasion, release bacterial products carcinogenic, suppression local immunity alteration tumor microenvironment. actual interactions between these role not yet fully understood. This review provides comprehensive overview hypotheses implicated ODIC, along with corresponding molecular aberrations. Apart from discussing usual microbiome profile, also summarizes profiles ODIC. sheds light on potential clinical implications research prevention management cancer.

Язык: Английский

Процитировано

0

Imbalance in gut microbial interactions as a marker of health and disease DOI Creative Commons
Roberto Corral López, Juan A. Bonachela, María Gloria Domínguez-Bello

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Апрель 30, 2025

Imbalances in the human gut microbiome (dysbioses) are linked to multiple diseases but remain poorly understood. Current biomarkers identify dysbiosis inconsistent and fail capture ecological mechanisms differentiating healthy from diseased microbiomes. We propose a general biomarker, inspired by phenomenology observed gut-microbiome theoretical model introduced here. The emergent communities show complex interaction networks two distinct collective states, corresponding dysbiotic Our robust metric for dysbiosis, quantifying balance between cooperation competition, differentiates these states both simulated real datasets across diverse diseases. Moreover, it reveals that results shift toward greater community. further correlates with disease progression, highlighting its potential as diagnostic tool.

Язык: Английский

Процитировано

0

Metaproteomics in the One Health framework for unraveling microbial effectors in microbiomes DOI Creative Commons

Robert Heyer,

M. Wolf, Dirk Benndorf

и другие.

Microbiome, Год журнала: 2025, Номер 13(1)

Опубликована: Май 23, 2025

Abstract One Health seeks to integrate and balance the health of humans, animals, environmental systems, which are intricately linked through microbiomes. These microbial communities exchange microbes genes, influencing not only human animal but also key environmental, agricultural, biotechnological processes. Preventing emergence pathogens as well monitoring controlling composition microbiomes effectors including virulence factors, toxins, antibiotics, non-ribosomal peptides, viruses holds transformative potential. However, mechanisms by these shape their broader functional consequences for host ecosystem remain poorly understood. Metaproteomics offers a novel methodological framework it provides insights into dynamics quantifying biomass composition, metabolic functions, detecting like viruses, antimicrobial resistance proteins, peptides. Here, we highlight potential metaproteomics in elucidating impact on discuss modulating foster desired functions. Graphical Word Cloud showing abundance keywords combination with “Microbiome” PubMed NCBI. As values, rounded logarithm base 2 hits were used submitted https://wordart.com/create . For microbiome, number without any was calculation. The word cloud displays different aspects microbiome research: (i.) sources (green), (ii.) interactions (purple), (iii.) involved taxa (red), (iv.) applied experimental approaches (blue), (vi.) societal effects recent or future applications (gray).

Язык: Английский

Процитировано

0

Creating microbiome-model harmony between metaproteomics data and the ADM1da for a two-step anaerobic digester DOI Creative Commons
Patrick Hellwig,

Ingolf Seick,

Nicole Meinusch

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 22, 2024

Abstract The effective operation, planning, and optimization of renewable energy production in anaerobic digestion (AD) plants relies on advanced process models, such as the Anaerobic Digestion Model No. 1 (ADM1). This study applies an ADM1-based model (ADM1da) to simulate a two-step digester industrial setting. data demonstrate that 2.6% methane is lost result open hydrolysis. Conversely, incorporation hydrolysis fermenter enhances by average 2.5%. Although ADM1-like models are widely recognized for accurately representing processes, mechanistic insights into microbiome involved have been limited absence tools analyze microbial composition functionality at time these were developed. To overcome this limitation, we utilized metaproteomics approach assess abundance biomass-correlated activity groups defined model, aiming bridge gap between ecology bioprocess engineering AD systems. We also developed evaluated series rules associating particular species with functional model. Our analysis demonstrates while supports presence stable main fermenter, it difficult capture dynamic behavior observed fermenter. Furthermore, actual displays greater versatility than assumes, microorganisms performing multiple functions rather being restricted single roles. In conclusion, identifies options improving integrating comprehensive biological knowledge further optimize performance digesters. Highlights Simulations revealed 2.6 % volume loss attributed Implementation increased 2.5% Identification map ADM1da depict but not Microbial perform just one assumed

Язык: Английский

Процитировано

0