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Address of the bookmark: https://dengue-lineages.org/

Before you go down that path, consider this critical biological question:
Are you sequencing human cells—or bacterial contamination?

The Silent Saboteur: Mycoplasma in Cell Cultures

Mycoplasma contamination remains one of the most widespread and underdiagnosed issues in tissue culture work. Studies suggest that 15–35% of cell lines in use may be contaminated, often without visible signs. Unlike other microbial infections, Mycoplasma does not produce cloudiness, odor, or a change in pH. Many researchers won’t detect it unless they specifically test for it.

The consequences, however, are profound. Mycoplasma can significantly alter:

• Host gene expression patterns

• Cell proliferation rates

• Epigenetic profiles and chromatin accessibility

• Cytokine signaling and immune responses

In short, it can skew your results, compromise your biological conclusions, and invalidate weeks or months of research.

A Simple Diagnostic Step: Map Against Mycoplasma Genomes

If you encounter poor alignment rates to the human genome, consider mapping your reads to a Mycoplasma reference genome—or better yet, use a combined human + Mycoplasma reference. There have been cases where over half of all reads, initially assumed to be from human cells, were in fact bacterial in origin. This check is fast, easy, and could save your project.

How Contamination Happens—and Persists

Mycoplasma is small (0.1–0.3 μm), lacks a cell wall, and can pass through standard filters undetected. Common sources include:

• Contaminated reagents (e.g., FBS)

• Infected cell lines obtained from other labs

• Poor aseptic technique or shared equipment

Once present, it spreads quickly between cultures and can persist for months, silently affecting results.

Why Treatment Is Difficult

While antibiotics such as Plasmocin or BM-Cyclin are sometimes used, they often offer only partial resolution and may themselves alter cell behavior. In many cases, the best course of action is to discard the contaminated culture and start with a fresh, verified stock.

Practical Recommendations for Researchers

• Routinely test for Mycoplasma using PCR, qPCR, or fluorescence-based assays

• Incorporate contamination screens into your sequencing QC pipeline

• Use combined reference genomes when mapping ambiguous reads

• Practice strict aseptic technique and monitor all incoming cell lines

• Don’t ignore unexplained data anomalies—they might point to contamination

Closing Thought: Contamination Is a Biological Variable

It’s easy to view poor mapping as a technical issue, but sometimes the problem lies deeper—in the biology itself. Mycoplasma contamination doesn’t just interfere with sequencing; it interferes with science. As a research community, we must treat contamination not as an afterthought, but as a key variable to control.

So next time your reads won’t align, don’t just tune the aligner. Ask if your cells are telling the truth—or if they're hiding something.

Department of Genetics

University of Delhi South Campus

NEW DELHI – 110 021

WALK-IN-INTERVIEW FOR THE TEMPORARY POSITIONS OF RESEACH SCIENTIT & LAB / FIELD ATTENDANT

1 Research Scientist (RS) – 3

DBT, Ph. D.

Experience on DNA Markers, plant genome mapping and bioinformatics

Salary: 60,000 (Consolidated) + 5% annual increment

Date and time: 25.06.2015 at 10:30 AM

These temporary positions have been sanctioned in a DBT funded project for the Phase II on ‘Centre of Excellence on genome mapping and molecular breeding of Brassicas.’

The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room.

Applicants are requested to bring all related documents, in original and a set of photocopy, for verification.

No TA/DA will be paid for attending the interview.

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Address of the bookmark: https://github.com/PapenfussLab/gridss

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As a computational genomicists our work involves examining billions of DNA base pairs and interpreting how variation impacts basic biology and disease. We develop computational methods and resources for the functional annotation of genomes with a special emphasis on sequencing-based assays (e.g. ChIP-seq, RNA-Seq, exome- and whole-genome sequencing, single-cell analysis).

http://www.computationalgenomics.ca

Link to working demo: https://vgteam.github.io/sequenceTubeMap/

Address of the bookmark: https://github.com/vgteam/sequenceTubeMap