#gene expression

[mindblowingscience]

Ever since the COVID-19 pandemic kicked off, we've been far more aware of our sense of smell. Now, new research shows that odors – like those emanating from ripening fruits or fermented foods – can lead to changes in how genes are expressed inside cells far beyond the nose. The findings have scientists wondering if, with much more research, sniffing volatile, airborne compounds could be a way to treat cancer or slow neurodegenerative disease.

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[cbirt]

Understanding cell dynamics, regulation, and characteristics has been revolutionized by profiling tests at a previously unheard-of resolution. Nevertheless, the destructive nature of these techniques makes it difficult to monitor the temporal dynamics of living cells. Although it lacks genetic and molecular interpretability, Raman microscopy offers a unique way to report vibrational energy levels at subcellular spatial resolution. The researchers created Raman2RNA (R2R), an experimental and computational framework that uses multi-modal data integration, domain translation, and label-free hyperspectral Raman microscopy images to infer single-cell expression patterns in living cells. 

Raman images were used to link scRNA-seq profiles to paired spatial hyperspectral Raman images, and machine learning models were trained to infer expression profiles from Raman spectra at the single-cell level. In reprogramming mouse fibroblasts into induced pluripotent stem cells (iPSCs), R2R accurately inferred the expression patterns of numerous cell stages and fates, including MET cells, iPSCs, stromal cells, fibroblasts, and epithelial cells. This demonstrates how crucial spectroscopic content is to Raman microscopy.

The dynamic balance of extrinsic and internal programs determines the states and functions of cells. Numerous genes work together to coordinate the expression and function of these activities, which include cell proliferation, stress responses, differentiation, and reprogramming. These genes also interact with other cells and the environment to influence these processes.

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[the-starry-lycan]

There is no context, and there will never be. The real context was the insulin we made along the way.

[bpod-bpod]

Entailed in Development

Hes gene activity, which oscillates, is crucial for differentiation of tissues in early embryo development. Here, Hes gene expression has been live-tracked in single cells of a developing mouse tail tip enabling its dynamics to be quantified for the first time

Read the published research article here

Video made with Leica Microsystems

Video from work by Yasmine el Azhar and colleagues

Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences), University Medical Center Utrecht, Utrecht, The Netherlands

Video originally published with a Creative Commons Attribution 4.0 International (CC BY 4.0)

Published in Development, September 2024

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[jcmarchi]

Machine learning and the microscope

New Post has been published on https://thedigitalinsider.com/machine-learning-and-the-microscope/

Machine learning and the microscope

With recent advances in imaging, genomics and other technologies, the life sciences are awash in data. If a biologist is studying cells taken from the brain tissue of Alzheimer’s patients, for example, there could be any number of characteristics they want to investigate — a cell’s type, the genes it’s expressing, its location within the tissue, or more. However, while cells can now be probed experimentally using different kinds of measurements simultaneously, when it comes to analyzing the data, scientists usually can only work with one type of measurement at a time.

Working with “multimodal” data, as it’s called, requires new computational tools, which is where Xinyi Zhang comes in.

The fourth-year MIT PhD student is bridging machine learning and biology to understand fundamental biological principles, especially in areas where conventional methods have hit limitations. Working in the lab of MIT Professor Caroline Uhler in the Department of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society, and collaborating with researchers at the Eric and Wendy Schmidt Center at the Broad Institute and elsewhere, Zhang has led multiple efforts to build computational frameworks and principles for understanding the regulatory mechanisms of cells.

“All of these are small steps toward the end goal of trying to answer how cells work, how tissues and organs work, why they have disease, and why they can sometimes be cured and sometimes not,” Zhang says.

The activities Zhang pursues in her down time are no less ambitious. The list of hobbies she has taken up at the Institute include sailing, skiing, ice skating, rock climbing, performing with MIT’s Concert Choir, and flying single-engine planes. (She earned her pilot’s license in November 2022.)

“I guess I like to go to places I’ve never been and do things I haven’t done before,” she says with signature understatement.

Uhler, her advisor, says that Zhang’s quiet humility leads to a surprise “in every conversation.”

“Every time, you learn something like, ‘Okay, so now she’s learning to fly,’” Uhler says. “It’s just amazing. Anything she does, she does for the right reasons. She wants to be good at the things she cares about, which I think is really exciting.”

Zhang first became interested in biology as a high school student in Hangzhou, China. She liked that her teachers couldn’t answer her questions in biology class, which led her to see it as the “most interesting” topic to study.

Her interest in biology eventually turned into an interest in bioengineering. After her parents, who were middle school teachers, suggested studying in the United States, she majored in the latter alongside electrical engineering and computer science as an undergraduate at the University of California at Berkeley.

Zhang was ready to dive straight into MIT’s EECS PhD program after graduating in 2020, but the Covid-19 pandemic delayed her first year. Despite that, in December 2022, she, Uhler, and two other co-authors published a paper in Nature Communications.

The groundwork for the paper was laid by Xiao Wang, one of the co-authors. She had previously done work with the Broad Institute in developing a form of spatial cell analysis that combined multiple forms of cell imaging and gene expression for the same cell while also mapping out the cell’s place in the tissue sample it came from — something that had never been done before.

This innovation had many potential applications, including enabling new ways of tracking the progression of various diseases, but there was no way to analyze all the multimodal data the method produced. In came Zhang, who became interested in designing a computational method that could.

The team focused on chromatin staining as their imaging method of choice, which is relatively cheap but still reveals a great deal of information about cells. The next step was integrating the spatial analysis techniques developed by Wang, and to do that, Zhang began designing an autoencoder.

Autoencoders are a type of neural network that typically encodes and shrinks large amounts of high-dimensional data, then expand the transformed data back to its original size. In this case, Zhang’s autoencoder did the reverse, taking the input data and making it higher-dimensional. This allowed them to combine data from different animals and remove technical variations that were not due to meaningful biological differences.

In the paper, they used this technology, abbreviated as STACI, to identify how cells and tissues reveal the progression of Alzheimer’s disease when observed under a number of spatial and imaging techniques. The model can also be used to analyze any number of diseases, Zhang says.

Given unlimited time and resources, her dream would be to build a fully complete model of human life. Unfortunately, both time and resources are limited. Her ambition isn’t, however, and she says she wants to keep applying her skills to solve the “most challenging questions that we don’t have the tools to answer.”

She’s currently working on wrapping up a couple of projects, one focused on studying neurodegeneration by analyzing frontal cortex imaging and another on predicting protein images from protein sequences and chromatin imaging.

“There are still many unanswered questions,” she says. “I want to pick questions that are biologically meaningful, that help us understand things we didn’t know before.”

[grrlscientist]

Diverse Headgear Of Hoofed Mammals Evolved From A Common Ancestor, study Baruch College & CUNY Graduate Center, published by Communications Biology

by @GrrlScientist

[covenawhite66]

Multiple species of Tardigrades are resistant to drought, high doses of radiation, low oxygen environments, and both high and low temperatures and pressures.

Tardigrades transform into a dormant state called anhydrobiosis, which allows them to reversibly halt their metabolism.

This is a study of Tardigrades genes that allows this.

A large amount of research has focused on the genetic pathways related to these capabilities, and a number of genes have been identified and linked to the extremotolerant response of tardigrades

This study generate the first phylogenies of six separate protein families linked with desiccation and radiation tolerance in Tardigrada

[dynamichealthinsights]

You Are Not Your Genes: How Lifestyle Choices Can Rewrite Your Biological Story

Imagine two identical twins, sharing the exact same DNA, yet one develops heart disease in their 50s while the other enjoys robust health well into their 80s. This scenario, while seemingly paradoxical, highlights the profound influence of epigenetics, a field revolutionizing our understanding of the interplay between genes and environment. Epigenetics, literally meaning “above genetics,”…

[cbirt]

The dynamic localization of thousands of unique regulatory proteins to specific DNA sequences regulates the expression of genes. It has been a longstanding objective of molecular biology to comprehend this cell-type specific mechanism. However, it is still difficult because the majority of DNA-protein mapping techniques only look at one protein at a time. 

A study was conducted to overcome this problem by a group of researchers who introduced a split-pool-based technique called ChIP-DIP (ChIP Done In Parallel), which allows hundreds of different regulatory proteins to be simultaneously mapped throughout the genome in a single experiment. Researchers show that all classes of DNA-associated proteins, such as transcription factors, RNA polymerases, chromatin regulators, and histone modifications, produce extremely accurate maps when generated by ChIP-DIP. By analyzing these data, scientists can identify different types of regulatory elements and their functional activity by defining quantitative combinations of protein localization on genomic DNA.

Thousands of regulatory proteins that localize at specific DNA sequences to activate, repress, and modulate transcription levels are involved in the regulation of gene expression specific to cell types. The Cell-type-specific chromatin states are defined by histone modifications and chromatin states, which are managed by chromatin regulators. These regulators regulate nucleosome location, DNA accessibility, and the reading, writing, and erasing of particular histone modifications. Molecular biology has spent decades trying to figure out how regulatory protein binding results in the expression of genes that are particular to a given cell type. The cell-type specificity of regulatory proteins and histone modifications’ interactions makes genome-wide mapping of these alterations difficult.

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[airises]

What are induced pluripotent stem cells, and how are they different from embryonic stem cells?

What are induced pluripotent stem cells (iPSCs)? Reprogrammed adult cells: iPSCs are created in the lab by taking adult cells (often skin or blood cells) and genetically reprogramming them back to an immature, embryo-like state. Pluripotency: Like embryonic stem cells, iPSCs are pluripotent. This means they have the exceptional potential to develop into almost any type of cell in the body. Key…

[bpod-bpod]

Sight Mapping

Identifying the tiny changes in DNA that might be causing disease is like trying to spot a single typo in a whole book. Figuring out how that change is having an impact is even harder. Researchers taking up this challenge for adult macular degeneration – a leading cause of blindness – focussed on cells in the eye called the retinal pigmented epithelium (RPE). They explored a protein called LHX2 (red in the composite image of mouse eye structures and lab-grown human cells) that influences gene expression in the RPE. Without LHX2, protein production dropped overall, and by mapping where LHX2 and another related protein (green) bind to DNA, they managed to pinpoint key genes involved in adult macular degeneration. Variation in the DNA influences how well LHX2 can bind, altering important gene expression and revealing details of macular degeneration risk, and potentially steering future research into new treatment approaches.

Written by Anthony Lewis

Images by Mazal Cohen-Gulkar, composite by Ruth Ashery-Padan

Research by Mazal Cohen-Gulkar, Ahuvit David, Naama Messika-Gold et al, Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine and Sagol School of Neurosciences, Tel Aviv University, Tel Aviv, Israel

Image originally published with a Creative Commons Attribution 4.0 International (CC BY 4.0)

Research published in PLOS Biology, January 2023

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[covenawhite66]

The same DNA is used in cells across the body but each type of cell has different functions. The different functions are from using different areas of a DNA strand to activate a specific gene.

Genetic loops regulate which genes are repressed in a cell not to be activated.

PRC1 and PRC2 are regulators that prevent developmental genes from becoming activated at the wrong time or in the wrong cell.

This was tested on a mouse embryo. A gene that affects cohesion was experimented with.

[alphaengineering]

Born Again🐐🧬

By:

[pebblegalaxy]

Unlocking the Mysteries of Gene Expression: From Genomic Imprinting to Non-Coding RNAs in Biology Class with Dr. Mishra

Unlocking the Mysteries of Gene Expression: From Genomic Imprinting to Non-Coding RNAs in Biology Class with Dr. Mishra #GeneExpression #BiologyClass #GenomicImprinting #NonCodingRNAs #CollaborativeLearning

Dr. Mishra: “Hello there! I see we have a new face in our biology class today. Welcome! We’re so glad you’re here, and I want you to know that this classroom is a friendly and supportive place. If you ever have questions or need assistance, don’t hesitate to ask me or your classmates. We’re all here to learn together and make this an enjoyable experience for you.” Abby: “Hello. My name is Abha…