Evidence map›Paper›PMID 42536049›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

De Novo Autogenic Engineered Living Functional Materials.

Hoda M Hammad, Seth Swarnadeep, Erin C Jackson, Nicolas Burns, Hongyu Wang, Harrison Priode, Robert B Moore, Sanket Deshmukh, Avinash Manjula-Basavanna, Anna M Duraj-Thatte

Abstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

10 authors.

Hoda M HammadDepartment of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0009-0007-6311-7993
Seth SwarnadeepDepartment of Chemical Engineering, Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0000-0001-7271-0704
Erin C JacksonMacromolecules Innovation Institute, Virginia Tech, Blacksburg, Virginia, USA.
Nicolas BurnsDepartment of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0000-0002-5885-2906
Hongyu WangInstitute For Critical Technology and Applied Science (ICTAS), Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0000-0002-6543-653X
Harrison PriodeDepartment of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0000-0002-7530-7969
Robert B MooreMacromolecules Innovation Institute, Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0000-0001-9057-7695
Sanket DeshmukhDepartment of Chemical Engineering, Virginia Tech, Blacksburg, Virginia, USA.
Avinash Manjula-BasavannaDepartment of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0000-0001-7806-2015
Anna M Duraj-ThatteDepartment of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia, USA.ORCID https://orcid.org/0000-0003-3814-2963

Funding

Emerging Frontiers in Research and InnovationInstitute for Critical Technology and Applied ScienceNational Science Foundation EFRI-ELiS program 2318093National Science Foundation Materials Innovation Platform 1933525Office of Emerging Frontiers and Multidisciplinary Activities
6 · The paper itself

Abstract

Autogenic engineered living materials (ELMs) enable the in situ production and engineering of native extracellular matrix (ECM). However, existing autogenic ELMs remain limited in scope and functionality. Here, we present a versatile platform for de novo autogenic functional ELMs, leveraging protein mining, computational modeling, and synthetic biology. By analyzing 33,564 CsgA-like homologs, we identify candidates for de novo ECM protein nanofibers. Using AlphaFold2 and molecular dynamics simulations, we elucidate the structural stability of these β-solenoid proteins. By reprogramming the Escherichia coli curli machinery, we achieve the biosynthesis of CsgA-like ELMs from non-model bacteria, featuring up to a 9-fold increased molecular weight and expanded β-sheet repeat units. Furthermore, we fabricate macroscopic biomaterials with enhanced mechanical properties (a 3-fold increase in storage modulus), and their extracellular fiber networks attenuate UV-C irradiation, extending the survival of embedded cells by 5-fold. We further demonstrate programmable functionalities, including 3D printability and selective binding to nanoparticles and antibodies. This work establishes a powerful framework for discovering, designing, and harnessing natural biomolecular systems to advance next-generation autogenic ELMs.

Indexed as

Biocompatible MaterialsEscherichia coli ProteinsExtracellular Matrix ProteinsEscherichia coliExtracellular MatrixHydrogelsMolecular Dynamics SimulationNanofibersProtein EngineeringBiocompatible MaterialscsgA protein, E coliEscherichia coli ProteinsExtracellular Matrix ProteinsHydrogelscurli nanofibersengineered living materialsfunctional amyloidsprotein hydrogelsprotein structure prediction

Identifiers

PMID42536049
PMCPMC13579223

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.