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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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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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There is no context, and there will never be. The real context was the insulin we made along the way.
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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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#science#biomedicine#immunofluorescence#biology#embryo development#developmental biology#gene expression
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The neuroscience lecture today was really fun. First about addiction, and then about depression. Discussing the neurochemical changes and how permanent they are. Changes in gene expression and nerve connections. Changes of brain anatomy. Not concerning at all.
....not that I have any of that. Anyway.
#roleplay#roleplayer#unilock roleplay#unilock#sherlock#roleplay blog#college#sherlock holmes#rp#sherlock headcanon#neuroscience#neurochemistry#chemistry major#chemistry#university#biology#gene expression#neuroanatomy#anatomy#science#addiction#depression
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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.”
#2022#amazing#Analysis#Animals#applications#Autoencoders#bioengineering#Biology#Brain#Broad Institute#cell#Cells#China#chromatin#communications#computer#Computer Science#covid#data#deal#december#Disease#Diseases#engine#engineering#form#Forms#Fundamental#gene expression#genes
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Diverse Headgear Of Hoofed Mammals Evolved From A Common Ancestor, study Baruch College & CUNY Graduate Center, published by Communications Biology
by @GrrlScientist
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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
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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,”…
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Nutrizione nei tumori: il delicato gioco metabolico di proteine, enzimi e metaboliti che coordina tutte le risposte cellulari
Background Dieta e nutrizione svolgono un ruolo fondamentale nella salute umana, con quantità, composizione e qualità della dieta, nonché orari dei pasti, fattori determinanti per la disponibilità di nutrienti che, a loro volta, regolano i processi fisiologici. Ricerche recenti si sono anche concentrate sulla comprensione di come la dieta influenzi le traiettorie delle malattie. Tuttavia, c’è…
#breast cancer#cancer cells#checkpoint therapy#gene expression#glucose metabolism#glutaminase#glutamine#glycolysis#immunotherapy#ketogenic diet#ketone bodies#microbiota#polyphenols#probiotics#protein kinase#protein phosphatase#short chain fatty acids#tumoral microenvironment#tyrosine kinase
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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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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…
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#biotechnology#Cell Therapy#Cellular Differentiation#Cellular Reprogramming#CRISPR#Developmental Biology#Embryonic Stem Cells#ESCs#Ethical Considerations#gene editing#Gene Expression#Immune Response#Induced Pluripotent Stem Cells#iPSCs#Medical Research#Pluripotency#Regenerative medicine#Stem Cell Research
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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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#science#biomedicine#neuroscience#retina#gene expression#age-related macular degeneration#macular degeneration#blindness#eyesight#immunofluorescence
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Bone marrow atlas offers new insights into blood cell development
- By Nuadox Crew -
Researchers at Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania have developed a new bone marrow atlas, published in the journal Cell.
Image credit: Cell (2024). DOI: 10.1016/j.cell.2024.04.013
This atlas provides a detailed view of the gene expression and spatial organization of bone marrow cells, offering insights into both healthy and diseased blood production. This study is a part of the larger Human BioMolecular Atlas Program (HuBMAP), which includes 42 research teams across multiple institutions and countries, working to advance molecular analysis technologies and create comprehensive tissue maps.
The research marks the first time that adult human bone marrow has been extensively profiled using single-cell RNA sequencing, which reveals the full gene expression of tens of thousands of individual cells.
This process helped identify nine subsets of non-hematopoietic (non-blood) cells, including three types previously unknown, which are involved in blood production and bone marrow health.
The atlas combines a transcriptional profile with a spatial map of bone marrow, created using a new technique called CODEX and machine learning, to show the arrangement of different cell types within the marrow.
The findings enhance understanding of bone marrow structure and function, and the technology used may lead to new diagnostics and treatments for bone marrow diseases, such as leukemia.
The research has the potential to significantly influence future studies and healthcare innovations related to bone marrow disorders.
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Source: The Children’s Hospital of Philadelphia
Full study: Shovik Bandyopadhyay et al, Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging, Cell (2024). DOI: 10.1016/j.cell.2024.04.013
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AI can help diagnose leukemia
#bone marrow#rna#gene expression#blood#medtech#ai#machine learning#genomics#codex#biotech#imaging#health tech#medicine#health
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New Light on Cells that Break Down Bone - Technology Org
New Post has been published on https://thedigitalinsider.com/new-light-on-cells-that-break-down-bone-technology-org/
New Light on Cells that Break Down Bone - Technology Org
Imaging technology developed at Garvan Institute shows that bone-resorbing osteoclasts gather in distinct pockets, leading to new insights for osteoporosis and cancer treatment.
Image of cells contained in a bone tissue. Image credit: Garvan Institute
Bone may seem like a hard, lifeless structure. Still, the cells living within have been imaged in unprecedented detail, thanks to an innovative imaging method developed at the Garvan Institute of Medical Research.
The new method lets researchers study cells inside the bones of mice, to visualise not just isolated sections, but the entire length of a bone. With a new level of visual detail, the researchers discovered that osteoclasts, cells that break down bone tissue, are more active in some parts of the bone than others.
This knowledge could be used to develop new treatments for osteoporosis, and for dormant cancer cells, which can stay hidden in bone for years until osteoclasts reactivate them.
“Our method has given us an unprecedented window into how cells go about breaking down bone, giving us a new way to investigate osteoporosis and cancer relapse in bone,” says Professor Tri Phan, Head of the Intravital Microscopy Lab and Gene Expression (IMAGE) Lab, immunologist at St Vincent’s Hospital Sydney, Co-Director of the Precision Immunology Program at Garvan and senior author of the paper, published in Nature Protocols.
“We can finally image processes inside bone that we thought were happening, but which were until now beyond the limits of conventional microscopy techniques. We are only beginning to understand the implications of this exciting technology.”
Picture of the bones in a human hand (from an authentic human skeleton). Image credit: Raul654 via Wikimedia, CC-BY-SA-3.0
Giving disease-causing cells no place to hide
Osteoclasts are crucial to the normal maintenance and repair processes of bone, but when they are overly active, they can cause excessive breakdown, known as osteoporosis.
“The inside of living bone is a ‘dark space’ that is difficult to study, because of its hard, mineralised structure,” says co-first author Dr Nayan Deger Bhattacharyya, post-doctoral researcher in the IMAGE Lab. “In order to understand diseases such as osteoporosis and cancer recurrence, we’ve needed to develop the technology to look inside bone tissue.”
The new technique developed at Garvan’s ACRF INCITe Centre can image other dynamic cellular processes until now hidden in bone.
“Our new imaging method is minimally invasive and lets us map out localised populations of cells along the length of an entire bone in our mouse models, instead of just in small sections,” says co-first author Wunna Kyaw, PhD student in the IMAGE Lab.
The researchers tracked down distinct pockets of bone resorption activity as the cells ‘morph’ between actively resorbing osteoclasts and an intermediate cell state called osteomorphs, in real time.
Osteoporosis in bones. Image credit: Scientific Animations, CC BY-SA 4.0
“We suspect these osteomorphs are dangerous as they can accumulate while osteoporosis treatment is administered but can rapidly reform activated osteoclasts to supercharge bone breakdown as soon as treatment is stopped.”
“This would explain an observation in the clinic, that many osteoporosis patients taking the medication denosumab, which blocks osteoclasts from resorbing bone, experience rebound vertebral fractures after they stop using the drug. We will use our imaging method to study how this withdrawal effect could be prevented,” says co-author Professor Peter Croucher, Head of the Bone Biology Lab at Garvan.
The researchers say their method could also be used to investigate cancer cells that can migrate to bone during cancer treatment and lie dormant there for years, only to be reactivated by osteoclasts breaking down the bone tissue surrounding them.
“Being able to see cells and molecules interact in the bone – and one day target them – could be a critical new tool for bone-related diseases,” says Professor Phan.
Source: Garvan Institute
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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.
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