Evidence map›Paper›PMID 19406900›Full record

ArticleMicrobiology (Reading, England)2009

Genomic DNA microarray comparison of gene expression patterns in Paracoccidioides brasiliensis mycelia and yeasts in vitro.

Jomar Patrício Monteiro, Karl V Clemons, Laurence F Mirels, John A Coller, Thomas D Wu, Jata Shankar, Catalina R Lopes, David A Stevens

Open access · greenAbstract read
In one paragraph

Article in Microbiology (Reading, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
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

14 citing papers in PubMed, 30 citations in OpenAlex.

  1. Review
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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

8 authors at 4 institutions in 2 countries.

Jomar Patrício MonteiroDepartment of Medicine, Division of Infectious Diseases, Santa Clara Valley Medical Center, San Jose, CA, USA.
Karl V ClemonsDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
Laurence F MirelsDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
John A CollerStanford Functional Genomics Facility, Stanford University, Stanford, CA, USA.
Thomas D WuBioinformatics Department, Genentech, Inc., South San Francisco, CA, USA.
Jata ShankarDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
Catalina R LopesGenetics Department, Biosciences Institute, UNESP, Botucatu, SP, Brazil.
David A StevensDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA.
California Institute for Medical Research · USStanford University · USUniversidade Estadual Paulista (Unesp) · BRSanta Clara Valley Medical Center · US

Funding

FIC NIH HHS 5D43TW923-5
6 · The paper itself

Abstract

Paracoccidioides brasiliensis is a thermally dimorphic fungus, and causes the most prevalent systemic mycosis in Latin America. Infection is initiated by inhalation of conidia or mycelial fragments by the host, followed by further differentiation into the yeast form. Information regarding gene expression by either form has rarely been addressed with respect to multiple time points of growth in culture. Here, we report on the construction of a genomic DNA microarray, covering approximately 25 % of the genome of the organism, and its utilization in identifying genes and gene expression patterns during growth in vitro. Cloned, amplified inserts from randomly sheared genomic DNA (gDNA) and known control genes were printed onto glass slides to generate a microarray of over 12,000 elements. To examine gene expression, mRNA was extracted and amplified from mycelial or yeast cultures grown in semi-defined medium for 5, 8 and 14 days. Principal components analysis and hierarchical clustering indicated that yeast gene expression profiles differed greatly from those of mycelia, especially at earlier time points, and that mycelial gene expression changed less than gene expression in yeasts over time. Genes upregulated in yeasts were found to encode proteins shown to be involved in methionine/cysteine metabolism, respiratory and metabolic processes (of sugars, amino acids, proteins and lipids), transporters (small peptides, sugars, ions and toxins), regulatory proteins and transcription factors. Mycelial genes involved in processes such as cell division, protein catabolism, nucleotide biosynthesis and toxin and sugar transport showed differential expression. Sequenced clones were compared with Histoplasma capsulatum and Coccidioides posadasii genome sequences to assess potentially common pathways across species, such as sulfur and lipid metabolism, amino acid transporters, transcription factors and genes possibly related to virulence. We also analysed gene expression with time in culture and found that while transposable elements and components of respiratory pathways tended to increase in expression with time, genes encoding ribosomal structural proteins and protein catabolism tended to sharply decrease in expression over time, particularly in yeast. These findings expand our knowledge of the different morphological forms of P. brasiliensis during growth in culture.

Indexed as

Gene Expression Regulation, FungalGenome, FungalMyceliumParacoccidioidesGene Expression ProfilingGenes, FungalHumansLatin AmericaMolecular Sequence DataOligonucleotide Array Sequence AnalysisParacoccidioidomycosisPrincipal Component AnalysisRNA, FungalRNA, MessengerTime FactorsRNA, FungalRNA, Messenger

Identifiers

PMID19406900
PMCPMC2888123
OpenAlexW2114485557

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.