ArticleApplied microbiology and biotechnology2026
Enhanced bacterial cellulose production by Komagataeibacter xylinus using agro-derived flour nitrogen sources.
Article in Applied microbiology and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Kombucha Bacterial Cellulose Obtained from Tea Fermentation for Biomedical Applications.ACS applied engineering materials · 2026Article
- Biocircular economy-driven bacterial cellulose with large pore size: statistical optimization using Glutamicibacter soli bread waste hydrolysate.Bioresources and bioprocessing · 2026Article
- Recent advances in bioengineering and functional applications of microbial biocomposites: integrating bacterial cellulose, fungal mycelium and synthetic biology.World journal of microbiology & biotechnology · 2026Review
- Techno-Economic and Statistical Assessment of Agricultural Flours for Bacterial Cellulose Production byPolymers · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacterial cellulose (BC) production is limited by the high cost of refined nitrogen sources such as yeast extract and tryptone. While carbon source substitution has been widely studied, approaches for nitrogen replacement remain underexplored. Here, we evaluated cereal and pseudo-cereal flours as low-cost nitrogen alternatives for Komagataeibacter xylinus DSMZ 2325 under static fermentation under static fermentation using two nitrogen substitution strategies: constant total nitrogen (CTN) and constant nitrogen source mass (CNSM). Thirteen flour variants were screened, with maximum BC yields of 3.40 g/L (soy), 3.17 g/L (teff), 2.74 g/L (quinoa), and 1.94 g/L (triticale) under the CTN strategy, in several cases surpassing the modified HS control. Structural analyses confirmed that flour-derived BC retained the defining characteristics of high-quality cellulose, including high crystallinity, robust fibrillar networks, and thermal stability. Soy consistently produced the highest volumetric yields, whereas triticale exhibited the greatest fold-increase compared to the control, highlighting the distinct nutritional and compositional contributions. These results demonstrate that flour-based media provide a viable strategy to reduce production costs while tailoring BC properties through substrate choice. By shifting the focus from carbon to nitrogen optimization, this study introduces a sustainable and scalable approach to bioprocessing using agro-derived raw materials. KEY POINTS: • Flour-based nitrogen sources replace costly yeast extract and tryptone in BC media • Triticale, teff, quinoa, and soy influence BC yield and cellulose fibril formation • Agro-flour substrates offer low-cost, sustainable bacterial cellulose production.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.