Evidence map›Paper›PMID 27485338›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2016

Small-Scale Screening to Large-Scale Over-Expression of Human Membrane Proteins for Structural Studies.

Sarika Chaudhary, Sukanya Saha, Sobrahani Thamminana, Robert M Stroud

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

4 authors.

Sarika ChaudharySystems Biology Group, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110025, India. sarika.chaudhary@igib.in.
Sukanya SahaSystems Biology Group, CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110025, India.
Sobrahani ThamminanaDepartment of Biochemistry and Biophysics, University of California at San Francisco, San Francisco, CA, 94158, USA.
Robert M StroudDepartment of Biochemistry and Biophysics, University of California at San Francisco, San Francisco, CA, 94158, USA. stroud@msg.ucsf.edu.

Funding

STRUCTURE/FUNCTION OF PROTEINS AT MOLECULAR LEVELR01GM024485 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STROUD, ROBERT M · 1985 to 2024
$7.5M
NIGMS NIH HHS R01 GM024485
6 · The paper itself

Abstract

Membrane protein structural studies are frequently hampered by poor expression. The low natural abundance of these proteins implies a need for utilizing different heterologous expression systems. E. coli and yeast are commonly used expression systems due to rapid cell growth at high cell density, economical production, and ease of manipulation. Here we report a simplified, systematically developed robust strategy from small-scale screening to large-scale over-expression of human integral membrane proteins in the mammalian expression system for structural studies. This methodology streamlines small-scale screening of several different constructs utilizing fluorescence size-exclusion chromatography (FSEC) towards optimization of buffer, additives, and detergents for achieving stability and homogeneity. This is followed by the generation of stable clonal cell lines expressing desired constructs, and lastly large-scale expression for crystallization. These techniques are designed to rapidly advance the structural studies of eukaryotic integral membrane proteins including that of human membrane proteins.

Indexed as

Chromatography, GelCloning, MolecularEscherichia coliGene ExpressionHEK293 CellsHumansMembrane ProteinsPlasmidsMembrane ProteinsFSECLarge-scale expressionMammalian cell cultureMembrane protein expression

Identifiers

PMID27485338
PMCPMC8367189

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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.