Skip to content
#protein folding Open access

Niche specialization and prevalence of comammox Nitrospira in the alkaline sediments of thermokarst lakes on the Tibetan Plateau

Sep 2026 · Nature Communications
Wastewater Treatment and Nitrogen Removal Microbial Community Ecology and Physiology

Abstract

Complete ammonia-oxidizing (comammox) Nitrospira are recognized as key players in the nitrogen cycle, yet their ecological roles in extreme environments remain poorly understood. Here, we show that comammox Nitrospira occupy distinct ecological niches in Tibetan Plateau thermokarst lakes (pH 7.5–10.2) using stable isotope probing, metagenomics, and metatranscriptomics. While gross nitrification rates are significantly higher in subalkaline lakes due to the active presence of ammonia-oxidizing archaea (AOA) and bacteria (AOB), these canonical nitrifiers are inhibited under elevated pH. In contrast, comammox Nitrospira activity is significantly higher in alkaline than in subalkaline lakes, becoming the predominant nitrifiers with activities exceeding those of AOA and AOB by over 6- and 15-fold, respectively. This niche transition, coupled with the inherently low N2O yield of comammox, results in significantly attenuated nitrous oxide (N2O) production in alkaline lakes. Under saline-alkaline stress, these bacteria maintained high expression of carbon fixation and sulfur metabolism genes while upregulating compatible solute biosynthesis, cation transporters, and protein chaperones. Altogether, these findings identify comammox bacteria as key mediators of nitrogen cycling in permafrost-affected thermokarst lakes, expanding their known physiological range and providing mechanistic insights into their adaptations to extreme environments. Researchers reveal that comammox Nitrospira become dominant nitrifiers in alkaline thermokarst lakes on the Tibetan Plateau and uncover their ecological adaptations to extreme saline-alkaline environments.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.