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Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use

Eight Subcellular Pathologies driving Chronic Metabolic Diseases – Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics: Impact on Pharmaceuticals in Use

Curators:

 

THE VOICE of Aviva Lev-Ari, PhD, RN

In this curation we wish to present two breaking through goals:

Goal 1:

Exposition of a new direction of research leading to a more comprehensive understanding of Metabolic Dysfunctional Diseases that are implicated in effecting the emergence of the two leading causes of human mortality in the World in 2023: (a) Cardiovascular Diseases, and (b) Cancer

Goal 2:

Development of Methods for Mapping Bioelectronic Adjustable Measurements as potential new Therapeutics for these eight subcellular causes of chronic metabolic diseases. It is anticipated that it will have a potential impact on the future of Pharmaceuticals to be used, a change from the present time current treatment protocols for Metabolic Dysfunctional Diseases.

According to Dr. Robert Lustig, M.D, an American pediatric endocrinologist. He is Professor emeritus of Pediatrics in the Division of Endocrinology at the University of California, San Francisco, where he specialized in neuroendocrinology and childhood obesity, there are eight subcellular pathologies that drive chronic metabolic diseases.

These eight subcellular pathologies can’t be measured at present time.

In this curation we will attempt to explore methods of measurement for each of these eight pathologies by harnessing the promise of the emerging field known as Bioelectronics.

Unmeasurable eight subcellular pathologies that drive chronic metabolic diseases

  1. Glycation
  2. Oxidative Stress
  3. Mitochondrial dysfunction [beta-oxidation Ac CoA malonyl fatty acid]
  4. Insulin resistance/sensitive [more important than BMI], known as a driver to cancer development
  5. Membrane instability
  6. Inflammation in the gut [mucin layer and tight junctions]
  7. Epigenetics/Methylation
  8. Autophagy [AMPKbeta1 improvement in health span]

Diseases that are not Diseases: no drugs for them, only diet modification will help

Image source

Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease

https://www.youtube.com/watch?v=Ee_uoxuQo0I

 

Exercise will not undo Unhealthy Diet

Image source

Robert Lustig, M.D. on the Subcellular Processes That Belie Chronic Disease

https://www.youtube.com/watch?v=Ee_uoxuQo0I

 

These eight Subcellular Pathologies driving Chronic Metabolic Diseases are becoming our focus for exploration of the promise of Bioelectronics for two pursuits:

  1. Will Bioelectronics be deemed helpful in measurement of each of the eight pathological processes that underlie and that drive the chronic metabolic syndrome(s) and disease(s)?
  2. IF we will be able to suggest new measurements to currently unmeasurable health harming processes THEN we will attempt to conceptualize new therapeutic targets and new modalities for therapeutics delivery – WE ARE HOPEFUL

In the Bioelecronics domain we are inspired by the work of the following three research sources:

  1. Biological and Biomedical Electrical Engineering (B2E2) at Cornell University, School of Engineering https://www.engineering.cornell.edu/bio-electrical-engineering-0
  2. Bioelectronics Group at MIT https://bioelectronics.mit.edu/
  3. The work of Michael Levin @Tufts, The Levin Lab
Michael Levin is an American developmental and synthetic biologist at Tufts University, where he is the Vannevar Bush Distinguished Professor. Levin is a director of the Allen Discovery Center at Tufts University and Tufts Center for Regenerative and Developmental Biology. Wikipedia
Born: 1969 (age 54 years), Moscow, Russia
Education: Harvard University (1992–1996), Tufts University (1988–1992)
Affiliation: University of Cape Town
Research interests: Allergy, Immunology, Cross Cultural Communication
Awards: Cozzarelli prize (2020)
Doctoral advisor: Clifford Tabin
Most recent 20 Publications by Michael Levin, PhD
SOURCE
SCHOLARLY ARTICLE
The nonlinearity of regulation in biological networks
1 Dec 2023npj Systems Biology and Applications9(1)
Co-authorsManicka S, Johnson K, Levin M
SCHOLARLY ARTICLE
Toward an ethics of autopoietic technology: Stress, care, and intelligence
1 Sep 2023BioSystems231
Co-authorsWitkowski O, Doctor T, Solomonova E
SCHOLARLY ARTICLE
Closing the Loop on Morphogenesis: A Mathematical Model of Morphogenesis by Closed-Loop Reaction-Diffusion
14 Aug 2023Frontiers in Cell and Developmental Biology11:1087650
Co-authorsGrodstein J, McMillen P, Levin M
SCHOLARLY ARTICLE
30 Jul 2023Biochim Biophys Acta Gen Subj1867(10):130440
Co-authorsCervera J, Levin M, Mafe S
SCHOLARLY ARTICLE
Regulative development as a model for origin of life and artificial life studies
1 Jul 2023BioSystems229
Co-authorsFields C, Levin M
SCHOLARLY ARTICLE
The Yin and Yang of Breast Cancer: Ion Channels as Determinants of Left–Right Functional Differences
1 Jul 2023International Journal of Molecular Sciences24(13)
Co-authorsMasuelli S, Real S, McMillen P
SCHOLARLY ARTICLE
Bioelectricidad en agregados multicelulares de células no excitables- modelos biofísicos
Jun 2023Revista Española de Física32(2)
Co-authorsCervera J, Levin M, Mafé S
SCHOLARLY ARTICLE
Bioelectricity: A Multifaceted Discipline, and a Multifaceted Issue!
1 Jun 2023Bioelectricity5(2):75
Co-authorsDjamgoz MBA, Levin M
SCHOLARLY ARTICLE
Control Flow in Active Inference Systems – Part I: Classical and Quantum Formulations of Active Inference
1 Jun 2023IEEE Transactions on Molecular, Biological, and Multi-Scale Communications9(2):235-245
Co-authorsFields C, Fabrocini F, Friston K
SCHOLARLY ARTICLE
Control Flow in Active Inference Systems – Part II: Tensor Networks as General Models of Control Flow
1 Jun 2023IEEE Transactions on Molecular, Biological, and Multi-Scale Communications9(2):246-256
Co-authorsFields C, Fabrocini F, Friston K
SCHOLARLY ARTICLE
Darwin’s agential materials: evolutionary implications of multiscale competency in developmental biology
1 Jun 2023Cellular and Molecular Life Sciences80(6)
Co-authorsLevin M
SCHOLARLY ARTICLE
Morphoceuticals: Perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging
1 Jun 2023Drug Discovery Today28(6)
Co-authorsPio-Lopez L, Levin M
SCHOLARLY ARTICLE
Cellular signaling pathways as plastic, proto-cognitive systems: Implications for biomedicine
12 May 2023Patterns4(5)
Co-authorsMathews J, Chang A, Devlin L
SCHOLARLY ARTICLE
Making and breaking symmetries in mind and life
14 Apr 2023Interface Focus13(3)
Co-authorsSafron A, Sakthivadivel DAR, Sheikhbahaee Z
SCHOLARLY ARTICLE
The scaling of goals from cellular to anatomical homeostasis: an evolutionary simulation, experiment and analysis
14 Apr 2023Interface Focus13(3)
Co-authorsPio-Lopez L, Bischof J, LaPalme JV
SCHOLARLY ARTICLE
The collective intelligence of evolution and development
Apr 2023Collective Intelligence2(2):263391372311683SAGE Publications
Co-authorsWatson R, Levin M
SCHOLARLY ARTICLE
Bioelectricity of non-excitable cells and multicellular pattern memories: Biophysical modeling
13 Mar 2023Physics Reports1004:1-31
Co-authorsCervera J, Levin M, Mafe S
SCHOLARLY ARTICLE
There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines
1 Mar 2023Biomimetics8(1)
Co-authorsBongard J, Levin M
SCHOLARLY ARTICLE
Transplantation of fragments from different planaria: A bioelectrical model for head regeneration
7 Feb 2023Journal of Theoretical Biology558
Co-authorsCervera J, Manzanares JA, Levin M
SCHOLARLY ARTICLE
Bioelectric networks: the cognitive glue enabling evolutionary scaling from physiology to mind
1 Jan 2023Animal Cognition
Co-authorsLevin M
SCHOLARLY ARTICLE
Biological Robots: Perspectives on an Emerging Interdisciplinary Field
1 Jan 2023Soft Robotics
Co-authorsBlackiston D, Kriegman S, Bongard J
SCHOLARLY ARTICLE
Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model
1 Jan 2023Entropy25(1)
Co-authorsShreesha L, Levin M
5

5 total citations on Dimensions.

Article has an altmetric score of 16
SCHOLARLY ARTICLE
1 Jan 2023BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY138(1):141
Co-authorsClawson WP, Levin M
SCHOLARLY ARTICLE
Future medicine: from molecular pathways to the collective intelligence of the body
1 Jan 2023Trends in Molecular Medicine
Co-authorsLagasse E, Levin M

THE VOICE of Dr. Justin D. Pearlman, MD, PhD, FACC

PENDING

THE VOICE of  Stephen J. Williams, PhD

Ten TakeAway Points of Dr. Lustig’s talk on role of diet on the incidence of Type II Diabetes

 

  1. 25% of US children have fatty liver
  2. Type II diabetes can be manifested from fatty live with 151 million  people worldwide affected moving up to 568 million in 7 years
  3. A common myth is diabetes due to overweight condition driving the metabolic disease
  4. There is a trend of ‘lean’ diabetes or diabetes in lean people, therefore body mass index not a reliable biomarker for risk for diabetes
  5. Thirty percent of ‘obese’ people just have high subcutaneous fat.  the visceral fat is more problematic
  6. there are people who are ‘fat’ but insulin sensitive while have growth hormone receptor defects.  Points to other issues related to metabolic state other than insulin and potentially the insulin like growth factors
  7. At any BMI some patients are insulin sensitive while some resistant
  8. Visceral fat accumulation may be more due to chronic stress condition
  9. Fructose can decrease liver mitochondrial function
  10. A methionine and choline deficient diet can lead to rapid NASH development

 

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Reporter: Danielle Smolyar, Research Assistant 3 – Text Analysis for 2.0 LPBI Group’s TNS #1 – 2020/2021 Academic Internship in Medical Test Analysis (MTA) 

Reporting on a Study published on July 6, 2021 by  Oregon Health & Science University

Recently, researchers have found many ways to manipulate and alter gene activity in specific cells. As a result of seeing this alteration, it has caused much development and progress in understanding cancer, brain function, and immunity.

IMAGE SOURCE: 3D-model of DNA. Credit: Michael Ströck/Wikimedia/ GNU Free Documentation Lic

Tissues and Organs are composed of cells that look the same but have different roles. For example, single-cell analysis allows us to research and test the cells within an organ or cancerous tumor. However, the single-cell study has its boundaries and limits in trying a more significant number of cells. This result is not an accurate data and analysis of the cells.

Andrew Adey, Ph.D., the senior author of a paper in Nature Biotechnology, https://www.nature.com/articles/s41587-021-00962-z

Mulqueen, R. M., Pokholok, D., O’Connell, B. L., Thornton, C. A., Zhang, F., O’Roak, B. J., Link, J., Yardımcı, G. G., Sears, R. C., Steemers, F. J., & Adey, A. C. (2021, July 5). High-content single-cell combinatorial indexing. Nature News. https://www.nature.com/articles/s41587-021-00962-z

states that the new method gives us the ability to have a ten-fold improvement in the amount of DNA produced from a single DNA sequence. A DNA sequence is composed of units which are called bases. The sequence puts the bases in chronological order for it to code correctly. 

To understand cancer better, single-cell studies are a crucial factor in doing so. Different cells catch on to other mutations in the DNA sequence in a cancerous tumor, which ultimately alters the DNA sequence. This results in tumor cells with new alterations, which could eventually spread to the rest of the body. 

Adey and his team provided evidence that the method they had created can show DNA alterations that have come from cells present in tumor samples from patients with pancreatic cancer. Adey stated,

quote “For example, you can potentially identify rare cell subtypes within a tumor that are resistant to therapy.” 

Abey and his team have been working with OHSU Knight Cancer Institute, and with them, they are testing a single-cell method to see if patients’ tumors have changed by doing chemo or drug therapy. 

This new method allows itself to create DNA libraries and fragments of DNA that helps analyze the different genes and mutations within the sequence. This method uses something called an enzymatic reaction that attaches primers to the end of each DNA fragment.  For the cells to be analyzed, each primer must be present on both ends of the fragment. 

As a result of this new method, all library fragments present must-have primers on both ends of the fragments. At the same time, it improves efficiency by reducing its sequencing  price overall, that these adapters can be used instead of the regular custom workflows. 

SOURCE

Original article:

Mulqueen, R.M., Pokholok, D., O’Connell, B.L. et al. High-content single-cell combinatorial indexing. Nat Biotechnol (2021). https://doi.org/10.1038/s41587-021-00962-z

Research categories – Cell biology, cancer-general, research, DNA Fragment TAGS- DNA, sequencing, cell fragments, single-cell

Other related articles published on this Open Access Online Scientific Journal include the following: 

Series B: Frontiers in Genomics Research

Series Content Consultant:

Larry H. Bernstein, MD, FCAP, Emeritus CSO, LPBI Group

Volume Content Consultant:

Prof. Marcus W. Feldman

BURNET C. AND MILDRED FINLEY WOHLFORD PROFESSOR IN THE SCHOOL OF HUMANITIES AND SCIENCES

Stanford University, Co-Director, Center for Computational, Evolutionary and Human Genetics (2012 – Present)

Latest in Genomics Methodologies for Therapeutics:

Gene Editing, NGS & BioInformatics,

Simulations and the Genome Ontology

2019

Volume Two

https://www.amazon.com/dp/B08385KF87

 

Part 4: Single Cell Genomics

Introduction to Part 4: Single Cell Genomics – Voice of Aviva Lev-Ari & Stephen Williams


4.1 The Science

4.1.1   Single-cell biology

Special | 05 July 2017

https://www.nature.com/collections/gbljnzchgg

4.1.2   The race to map the human body — one cell at a time, A host of detailed cell atlases could revolutionize understanding of cancer and other diseases

https://www.nature.com/news/the-race-to-map-the-human-body-one-cell-at-a-time-1.21508

4.1.3   Single-cell Genomics: Directions in Computational and Systems Biology – Contributions of Prof. Aviv Regev @Broad Institute of MIT and Harvard, Cochair, the Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute

Curator: Aviva Lev-Ari, PhD, RN

4.1.4   Cellular Genetics

https://www.sanger.ac.uk/science/programmes/cellular-genetics

4.1.5   Cellular Genomics

https://www.garvan.org.au/research/cellular-genomics

4.1.6   SINGLE CELL GENOMICS 2019 – sometimes the sum of the parts is greater than the whole, September 24-26, 2019, Djurönäset, Stockholm, Sweden http://www.weizmann.ac.il/conferences/SCG2019/single-cell-genomics-2019

Reporter: Aviva Lev-Ari, PhD, RN

4.1.7   Norwich Single-Cell Symposium 2019, Earlham Institute, single-cell genomics technologies and their application in microbial, plant, animal and human health and disease, October 16-17, 2019, 10AM-5PM

Reporter: Aviva Lev-Ari, PhD, RN

4.1.8   Newly Found Functions of B Cell

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

4.1.9 RESEARCH HIGHLIGHTS: HUMAN CELL ATLAS

https://www.broadinstitute.org/research-highlights-human-cell-atlas

4.2 Technologies and Methodologies

4.2.1   How to build a human cell atlas – Aviv Regev is a maven of hard-core biological analyses. Now she is part of an effort to map every cell in the human body.

Anna Nowogrodzki, 05 July 2017, Article tools

https://www.nature.com/news/how-to-build-a-human-cell-atlas-1.22239

4.2.2   Featuring Computational and Systems Biology Program at Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute (SKI), The Dana Pe’er Lab

Reporter: Aviva Lev-Ari, PhD, RN

4.2.3   Genomic Diagnostics: Three Techniques to Perform Single Cell Gene Expression and Genome Sequencing Single Molecule DNA Sequencing

Curator: Aviva Lev-Ari, PhD, RN

4.2.4   Three Technology Leaders in Single Cell Sequencing: 10X Genomics, Illumina and MissionBio

Reporter: Aviva Lev-Ari, PhD, RN

4.2.5   scPopCorn: A New Computational Method for Subpopulation Detection and their Comparative Analysis Across Single-Cell Experiments

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

4.2.6   Nano-guided cell networks: new methods to detect intracellular signaling and implications

Curator: Stephen J. Williams, PhD

4.3 Clinical Aspects

4.3.1 Using single cell sequencing data to model the evolutionary history of a tumor.

Kim KI, Simon R.

BMC Bioinformatics. 2014 Jan 24;15:27. doi: 10.1186/1471-2105-15-27.

PMID:

4.3.2   eProceedings 2019 Koch Institute Symposium – 18th Annual Cancer Research Symposium – Machine Learning and Cancer, June 14, 2019, 8:00 AM-5:00 PM ET MIT Kresge Auditorium, 48 Massachusetts Ave, Cambridge, MA

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

4.3.3   The Impact of Heterogeneity on Single-Cell Sequencing

Samantha L. Goldman1,2, Matthew MacKay1,2, Ebrahim Afshinnekoo1,2,3, Ari M. Melnick4, Shuxiu Wu5,6 and Christopher E. Mason1,2,3,7*

https://www.frontiersin.org/articles/10.3389/fgene.2019.00008/full

4.3.4   Single-cell approaches to immune profiling

https://www.nature.com/articles/d41586-018-05214-w

4.3.5   Single-cell sequencing made simple. Data from thousands of single cells can be tricky to analyse, but software advances are making it easier.

by Jeffrey M. Perkel

https://www.nature.com/news/single-cell-sequencing-made-simple-1.22233

4.3.6  Single-cell RNA-seq helps in finding intra-tumoral heterogeneity in pancreatic cancer

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

4.3.7 Cancer Genomics: Multiomic Analysis of Single Cells and Tumor Heterogeneity

Curator: Stephen J. Williams, PhD

4.4 Business and Legal

4.4.1   iBioChips integrate diagnostic assays and cellular engineering into miniaturized chips that achieve cutting-edge sensitivity and high-throughput. We have resolved traditional biotech challenges with innovative biochip approaches

https://ibiochips.com/?gclid=Cj0KCQjwuLPnBRDjARIsACDzGL0wb6u79VHHkftodfApMYs-oxI-5cOZIBUaELdmd2wDOIk3W0OQg2caAqMyEALw_wcB

4.4.2   Targeted Single-Cell Solutions for High Impact Applications – Mission Bio’s Tapestri® Platform is the only technology that provides single-cell targeted DNA sequencing at single-base resolution.

Part 4: Summary – Single Cell Genomics – Voice of Stephen Williams

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