Evidence map›Paper›PMID 42871668›Full record

ReviewFrontiers in bioengineering and biotechnology2026

Programmable synthetic engineering of adaptive microbial cell factories: from amide transforming enzymes to advanced biocatalytic systems.

Syeda Warisul Fatima, Shahenvaz Alam

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Syeda Warisul FatimaWinship Cancer Institute, School of Medicine, Emory University, Atlanta, GA, United States.
Shahenvaz AlamEmory Musculoskeletal Institute, School of Medicine, Emory University, Atlanta, GA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial cell factories integrate metabolic engineering, synthetic regulation, protein engineering, and computational design to improve catalytic performance and process robustness. Within this landscape, amide transforming enzymes provide diverse functions ranging from nitrogen metabolism and hydrolysis to covalent protein remodeling. This review examines amidases, asparaginases, glutaminases, nitrilases, nitrile hydratases, acylases, and carbamylases, with particular emphasis on microbial transglutaminase (MTGase). MTGase is distinguished by its ability to catalyze covalent ε-(γ-glutamyl) lysine crosslinking through acyl transfer reactions, enabling protein stabilization, molecular assembly, immobilization, and spatial organization of catalytic systems. This review critically examines the transition from classical amide transforming enzymes toward engineered biocatalytic systems and evaluates how MTGase could be leveraged as a protein level control component in microbial cell factories. Experimental developments in MTGase production, structural and protein engineering, synthetic genetic circuits, CRISPR based regulation, metabolic control, nanobiomaterials, and spatial biocatalysis are evaluated alongside computational approaches including AlphaFold assisted structure prediction, molecular docking, molecular dynamics, machine learning guided mutagenesis, and metabolic modeling. Emphasis is placed on experimentally validated outcomes and current limitations. Key unresolved barriers include intracellular off target crosslinking, proteostatic burden, variable crosslink stoichiometry, limited temporal control of MTGase activity, chassis dependence, and industrial scale up. Where direct evidence is lacking, prospective applications are distinguished from established capabilities and corresponding engineering strategies are proposed. Collectively, this review envisions MTGase as a controllable protein level platform for synthetic biology, while defining the evidence, limitations, and experimental requirements needed for its broader application in microbial biotechnology.

Indexed as

adaptive biofactoriesartificial intelligence, guided protein engineeringmetabolic engineeringmicrobial cell factoriesmicrobial enzymesprogrammable biocatalysis

Identifiers

PMID42871668
PMCPMC13658986

What OpenQuestion holds

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Registered trials

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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.