One of the applications of E. coli genome-scale model is in the biological discovery of underground metabolic functions of partially characterized genes and/or enzymes. Here we report for the first time, a failed prediction of atpE gene knockout of no growth in the most recent E. coli reconstruction iJ01366 model, and a positive experimental growth on glucose, enabling a model-driven biological discovery of the underground metabolic function of this gene in E. coli metabolism. These findings unfolded what could be described as either scope gaps in the reconstruction or true biological gaps (knowledge gaps) on the missing atpE gene function in E. coli metabolism. This study informs other studies that the gaps could be pursued into the E. coli metabolism, leading to a model-driven discovery in the future. This can be achieved by using gap filling algorithms (such as GrowMatch, SMILEY
Optimization of experimental protocols for cellular lysisExpedeon
In this project, we have compared existing sample preparation methods for proteomics studies against newly developed FASP method and our in-house developed SDS-TCA protocol. For our
preliminary studies, we have chosen a very well characterized soil microbe Pseudomonas putida.
Search for atoxic cereals: a single blind, cross-over study on the safety of...Enrique Moreno Gonzalez
Cereals of baking quality with absent or reduced toxicity are actively sought as alternative therapy to a gluten-free diet (GFD) for patients with coeliac disease (CD). Triticum monococcum, an ancient wheat, is a potential candidate having no toxicity in in-vitro and exvivo studies. The aim of our study was to investigate on the safety of administration of a single dose of gluten of Tm in patients with CD on GFD.
Optimization of experimental protocols for cellular lysisExpedeon
In this project, we have compared existing sample preparation methods for proteomics studies against newly developed FASP method and our in-house developed SDS-TCA protocol. For our
preliminary studies, we have chosen a very well characterized soil microbe Pseudomonas putida.
Search for atoxic cereals: a single blind, cross-over study on the safety of...Enrique Moreno Gonzalez
Cereals of baking quality with absent or reduced toxicity are actively sought as alternative therapy to a gluten-free diet (GFD) for patients with coeliac disease (CD). Triticum monococcum, an ancient wheat, is a potential candidate having no toxicity in in-vitro and exvivo studies. The aim of our study was to investigate on the safety of administration of a single dose of gluten of Tm in patients with CD on GFD.
Purification of G-Protein Coupled Receptor from Membrane Cell of Local Strain...iosrjce
The aim of this study to purify GPCR from a local strain of S. cerevisiae using gel filtration
chromatography techniques , by packing materials for columns which will be chosen of low cost comparing to
the already used in published researches, which depend on the costly affinity chromatography and other
expensive methods of purification. Local strain of S. cerevisiae chosen for extraction and purification of Gprotein
coupled receptor (GPCR) .The strains were obtained from biology department in Al- Mosul University,
Iraq. The isolated colony was activated on Yeast Extract Pepton Dextrose Broth (YEPDB) and incubated at 30
C˚ for 24 h .Loop fully of the yeast culture was transferred to (10ml) of yeast extract peptone glucose agar
(YEPGA) slant , then incubated at 30C˚for 24h , after that it was stored at 4C˚ ,the yeast cultures were
reactivated and persevered after each two weeks period. S.cerevisiae was identified by morphological,
microscopic characterization and biochemical test . The GPCR that extract from membrane of S.cerevisiae was
purified by gel filtration chromatography in two steps using Sepharose 6B. The optical density for each fraction
was measured at 280 nm by UV-VS spectrophotometer then the GPCR concentration was determined by using
ELISA Kit . The fractions which gave the highest absorbance and concentration of GPCR were collected .The
molecular weight of GPCR was determined by gel filtration chromatography using blue dextrin solution.
Standard curve was plotted between log of molecular weight for standard protein and the ratio of Ve/Vo of
GPCR . The purity of the GPCR that extracted and purified from whole cell of S, cerevisiae were carried out by
using SDS-PAGE electrophoresis In the first step 5ml of crude extract was applied on sepharose 6B column
(1.6x 96 cm) which previously equilibrated with 50 mM phosphate buffer saline pH= 7.4 . Multiple proteins
peaks appeared after elution with elution buffer (PBS PH= 7.4 containing 0. 5 % DDM). One peak only give
positive result with GPCR assay, fractions representing GPCR were collected , pooled and concentrated by
sucrose. In the second step five active fractions from the previous step were collected and applied once again on
the same column and same conditions. This step gave a single peak that was identical with the peak of GPCR
concentration ,maximum concentration of GPCR that observed in the fractions (34-38) was 18.541 (ng/ml) . The
specific activity for these fractions was 261.14 (ng/mg) protein with yield of 47.717%. The present study a chive
a relatively high purification of GPCR from membrane fraction of a local strain S. cerevisiae with fold
purification 5.094 and a yield of 47.717%. and molecular weight about~55KD.
Antioxidant-mediated up-regulation of OGG1 via NRF2 induction is associated ...Enrique Moreno Gonzalez
Estrogen metabolism-mediated oxidative stress is suggested to play an important role in estrogen-induced breast carcinogenesis. We have earlier demonstrated that antioxidants,
vitamin C (Vit C) and butylated hydroxyanisole (BHA) inhibit 17β-estradiol (E2)-mediated oxidative stress and oxidative DNA damage, and breast carcinogenesis in female August
Copenhagen Irish (ACI) rats. The objective of the present study was to characterize the mechanism by which above antioxidants prevent DNA damage during breast carcinogenesis.
ADAR2 editing activity in newly diagnosed versus relapsed pediatric high-grad...Enrique Moreno Gonzalez
High-grade (WHO grade III and IV) astrocytomas are aggressive malignant brain tumors affecting humans with a high risk of recurrence in both children and adults. To date, limited information is available on the genetic and molecular alterations important in the onset and progression of pediatric high-grade astrocytomas and, even less, on the prognostic factors that influence long-term outcome in children with recurrence. A-to-I RNA editing is an essential post-transcriptional mechanism that can alter the nucleotide sequence of several RNAs and is
mediated by the ADAR enzymes. ADAR2 editing activity is particularly important in mammalian brain and is impaired in both adult and pediatric high-grade astrocytomas.
Moreover, we have recently shown that the recovered ADAR2 activity in high-grade astrocytomas inhibits in vivo tumor growth. The aim of the present study is to investigate whether changes may occur in ADAR2-mediated RNA editing profiles of relapsed highgrade astrocytomas compared to their respective specimens collected at diagnosis, in four pediatric patients.
Protein Protein Interactions Of Glycine Oxidase (Thi O)bturne
Project done as a final presentation for Experimental Biochemistry. The project was designed and proposed by me and performed by myself and Lauren Pioppo.
Historically, genetic toxicology has been comprised of bacterial and cell based in vitro assays such as the Ames assay (a bacterial mutagenicity assay), Micronucleus and Chromosomal Aberration assays (mammalian cytogenetic assays), and Mouse Lymphoma Assay (in vitro mammalian cell gene mutation assay). These were routinely used for safety evaluation and are still part of the standard core battery. The emergence of new technologies has facilitated the development of in vitro methods for safe and effective drug and chemical testing.
This BioReliance® toxicology services webinar will explore alternative models, including 3D skin models that comply with the EC Scientific Committee on Consumer Safety (SCCS) recommendations. It will also discuss how the 3Rs (Replace, Reduce, Refine) Principle advocates the exploration of such alternative methods while achieving required goals.
In this webinar, you will learn:
• About in vitro alternatives to animal toxicity testing in pharma, chemical, tobacco, and personal care products.
• How the 3Rs (Replace, Reduce, Refine) Principle advocates exploring alternative methods without compromising the required goals.
• Alternatives to comply with the 7th Amendment to the EC Cosmetics Directive.
Purification of G-Protein Coupled Receptor from Membrane Cell of Local Strain...iosrjce
The aim of this study to purify GPCR from a local strain of S. cerevisiae using gel filtration
chromatography techniques , by packing materials for columns which will be chosen of low cost comparing to
the already used in published researches, which depend on the costly affinity chromatography and other
expensive methods of purification. Local strain of S. cerevisiae chosen for extraction and purification of Gprotein
coupled receptor (GPCR) .The strains were obtained from biology department in Al- Mosul University,
Iraq. The isolated colony was activated on Yeast Extract Pepton Dextrose Broth (YEPDB) and incubated at 30
C˚ for 24 h .Loop fully of the yeast culture was transferred to (10ml) of yeast extract peptone glucose agar
(YEPGA) slant , then incubated at 30C˚for 24h , after that it was stored at 4C˚ ,the yeast cultures were
reactivated and persevered after each two weeks period. S.cerevisiae was identified by morphological,
microscopic characterization and biochemical test . The GPCR that extract from membrane of S.cerevisiae was
purified by gel filtration chromatography in two steps using Sepharose 6B. The optical density for each fraction
was measured at 280 nm by UV-VS spectrophotometer then the GPCR concentration was determined by using
ELISA Kit . The fractions which gave the highest absorbance and concentration of GPCR were collected .The
molecular weight of GPCR was determined by gel filtration chromatography using blue dextrin solution.
Standard curve was plotted between log of molecular weight for standard protein and the ratio of Ve/Vo of
GPCR . The purity of the GPCR that extracted and purified from whole cell of S, cerevisiae were carried out by
using SDS-PAGE electrophoresis In the first step 5ml of crude extract was applied on sepharose 6B column
(1.6x 96 cm) which previously equilibrated with 50 mM phosphate buffer saline pH= 7.4 . Multiple proteins
peaks appeared after elution with elution buffer (PBS PH= 7.4 containing 0. 5 % DDM). One peak only give
positive result with GPCR assay, fractions representing GPCR were collected , pooled and concentrated by
sucrose. In the second step five active fractions from the previous step were collected and applied once again on
the same column and same conditions. This step gave a single peak that was identical with the peak of GPCR
concentration ,maximum concentration of GPCR that observed in the fractions (34-38) was 18.541 (ng/ml) . The
specific activity for these fractions was 261.14 (ng/mg) protein with yield of 47.717%. The present study a chive
a relatively high purification of GPCR from membrane fraction of a local strain S. cerevisiae with fold
purification 5.094 and a yield of 47.717%. and molecular weight about~55KD.
Antioxidant-mediated up-regulation of OGG1 via NRF2 induction is associated ...Enrique Moreno Gonzalez
Estrogen metabolism-mediated oxidative stress is suggested to play an important role in estrogen-induced breast carcinogenesis. We have earlier demonstrated that antioxidants,
vitamin C (Vit C) and butylated hydroxyanisole (BHA) inhibit 17β-estradiol (E2)-mediated oxidative stress and oxidative DNA damage, and breast carcinogenesis in female August
Copenhagen Irish (ACI) rats. The objective of the present study was to characterize the mechanism by which above antioxidants prevent DNA damage during breast carcinogenesis.
ADAR2 editing activity in newly diagnosed versus relapsed pediatric high-grad...Enrique Moreno Gonzalez
High-grade (WHO grade III and IV) astrocytomas are aggressive malignant brain tumors affecting humans with a high risk of recurrence in both children and adults. To date, limited information is available on the genetic and molecular alterations important in the onset and progression of pediatric high-grade astrocytomas and, even less, on the prognostic factors that influence long-term outcome in children with recurrence. A-to-I RNA editing is an essential post-transcriptional mechanism that can alter the nucleotide sequence of several RNAs and is
mediated by the ADAR enzymes. ADAR2 editing activity is particularly important in mammalian brain and is impaired in both adult and pediatric high-grade astrocytomas.
Moreover, we have recently shown that the recovered ADAR2 activity in high-grade astrocytomas inhibits in vivo tumor growth. The aim of the present study is to investigate whether changes may occur in ADAR2-mediated RNA editing profiles of relapsed highgrade astrocytomas compared to their respective specimens collected at diagnosis, in four pediatric patients.
Protein Protein Interactions Of Glycine Oxidase (Thi O)bturne
Project done as a final presentation for Experimental Biochemistry. The project was designed and proposed by me and performed by myself and Lauren Pioppo.
Historically, genetic toxicology has been comprised of bacterial and cell based in vitro assays such as the Ames assay (a bacterial mutagenicity assay), Micronucleus and Chromosomal Aberration assays (mammalian cytogenetic assays), and Mouse Lymphoma Assay (in vitro mammalian cell gene mutation assay). These were routinely used for safety evaluation and are still part of the standard core battery. The emergence of new technologies has facilitated the development of in vitro methods for safe and effective drug and chemical testing.
This BioReliance® toxicology services webinar will explore alternative models, including 3D skin models that comply with the EC Scientific Committee on Consumer Safety (SCCS) recommendations. It will also discuss how the 3Rs (Replace, Reduce, Refine) Principle advocates the exploration of such alternative methods while achieving required goals.
In this webinar, you will learn:
• About in vitro alternatives to animal toxicity testing in pharma, chemical, tobacco, and personal care products.
• How the 3Rs (Replace, Reduce, Refine) Principle advocates exploring alternative methods without compromising the required goals.
• Alternatives to comply with the 7th Amendment to the EC Cosmetics Directive.
It is easy to fall victim to discounting. The amazing short term benefits are very attractive, but it destroys the long term sustainability of your store. Here are the dangers of discounting and how to avoid them.
How to Build the Perfect VIP Program, and Why You Should!Smile.io
Learn why a VIP program is an effective way to drive sales and customer loyalty for your business. We will walk you through how to build the best program possible, with some examples along the way.
Why Repeat Customers Are the Best CustomersSmile.io
Repeat customers are responsible for more than 40% of a store’s annual revenue, and retention strategies are the perfect way to get the most out of these amazing shoppers. But did you know they’re worth so much more than that?
Mitochondria and nucleus maintain collaboration during apoptosis and oncogenesis where two machineries FEN1 and ING1 are playing major role in the theatre of DNA metabolic pathway in concomitant with the metabolic actor PCNA. PCNA, FEN1 and ING1 localized in mitochondria and nucleus by forming a larger protein complex, potentially involved in the regulation of DNA damage repair, apoptosis and cancer. But the mechanism of these proteins migration and coordination between mitochondria and nucleus is unknown. Understanding the signaling across sub-cellular location based on FEN1/ING1/PCNA might lead to interlink the molecular regulation of cell death and immortalization within the mitochondrial and nuclear location.
Building Loyalty Programs for Men and WomenSmile.io
Even though men and women have dramatically different characteristics, there are ways you can bridge the gap! Customer loyalty is the perfect tool for drawing people to your brand, especially when your program is designed to appeal to everyone.
The IOSR Journal of Pharmacy (IOSRPHR) is an open access online & offline peer reviewed international journal, which publishes innovative research papers, reviews, mini-reviews, short communications and notes dealing with Pharmaceutical Sciences( Pharmaceutical Technology, Pharmaceutics, Biopharmaceutics, Pharmacokinetics, Pharmaceutical/Medicinal Chemistry, Computational Chemistry and Molecular Drug Design, Pharmacognosy & Phytochemistry, Pharmacology, Pharmaceutical Analysis, Pharmacy Practice, Clinical and Hospital Pharmacy, Cell Biology, Genomics and Proteomics, Pharmacogenomics, Bioinformatics and Biotechnology of Pharmaceutical Interest........more details on Aim & Scope).
In Vivo Precision Genetic Change of Soybean Δ9-Stearoyl (18:0)-ACP Desaturase...IIJSRJournal
Altering genes in their native environment is a powerful tool for biologists and breeders to study gene function and to genetically modify or redesign plant metabolism toward production of specific higher –value products. Even though gene targeting has been widely applied in organisms such as yeast and mammals, its efficiency in plants still is not high enough for routine application. The strategy used in this work consists of using ssDNA oligonucleotide–directed gene targeting to generate a site-specific base conversion or amino acid conversion in the soybean Δ9-stearoyl (18:0)-ACP desaturase and ALS (acetolactate synthase) genes to make the former specific to (16:0)-ACP (in order to produce 16:1) and the latter to make it resistant to a sulfonurea herbicide (for selection). In the same manner, yeast Saccharomyces cerevisiae was used as a model to test the approach since advantages of using such a model were well recognized. Though there were reports of success and reproducibility of such an approach in certain agronomical crops where most targeted genes for repair were transient plasmid genes or episomal genes (Gamper, 2000), this was the first time such a strategy was applied to soybean. The approach was not a success with the soybean; however, positive results were recorded with the yeast model.
Molecular Identification of Specific Virulence Genes in EnteropathogenicEsche...iosrjce
IOSR Journal of Pharmacy and Biological Sciences(IOSR-JPBS) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of Pharmacy and Biological Science. The journal welcomes publications of high quality papers on theoretical developments and practical applications in Pharmacy and Biological Science. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The IOSR Journal of Pharmacy (IOSRPHR) is an open access online & offline peer reviewed international journal, which publishes innovative research papers, reviews, mini-reviews, short communications and notes dealing with Pharmaceutical Sciences( Pharmaceutical Technology, Pharmaceutics, Biopharmaceutics, Pharmacokinetics, Pharmaceutical/Medicinal Chemistry, Computational Chemistry and Molecular Drug Design, Pharmacognosy & Phytochemistry, Pharmacology, Pharmaceutical Analysis, Pharmacy Practice, Clinical and Hospital Pharmacy, Cell Biology, Genomics and Proteomics, Pharmacogenomics, Bioinformatics and Biotechnology of Pharmaceutical Interest........more details on Aim & Scope).
All manuscripts are subject to rapid peer review. Those of high quality (not previously published and not under consideration for publication in another journal) will be published without delay.
The targeted recognition of Lactococcus lactis phages tothei.docxarnoldmeredith47041
The targeted recognition of Lactococcus lactis phages to
their polysaccharide receptors
Orla McCabe,1† Silvia Spinelli,2,3† Carine Farenc,2,3
Myriam Labbé,4,5 Denise Tremblay,4
Stéphanie Blangy,2,3 Stefan Oscarson,1*
Sylvain Moineau4,5 and Christian Cambillau2,3*
1Centre for Molecular Innovation and Drug Discovery,
School of Chemistry and Chemical Biology, University
College Dublin, Belfield, Dublin, Ireland.
2Architecture et Fonction des Macromolécules
Biologiques, CNRS, Marseille, UMR 7257, France.
3Aix-Marseille University, Campus de Luminy, Case
932, Marseille, 13288 France.
4Groupe de recherche en écologie buccale & Félix
d’Hérelle Reference Center for Bacterial Viruses,
Faculté de médecine dentaire, Université Laval,
Québec, G1V 0A6, Canada.
5Département de biochimie, de microbiologie et de
bio-informatique, Faculté des sciences et de génie,
Université Laval, Québec, G1V 0A6, Canada.
Summary
Each phage infects a limited number of bacterial
strains through highly specific interactions of the
receptor-binding protein (RBP) at the tip of phage tail
and the receptor at the bacterial surface. Lactococcus
lactis is covered with a thin polysaccharide pellicle
(hexasaccharide repeating units), which is used by a
subgroup of phages as a receptor. Using L. lactis and
phage 1358 as a model, we investigated the interaction
between the phage RBP and the pellicle hexasaccha-
ride of the host strain. A core trisaccharide (TriS),
derived from the pellicle hexasaccharide repeating
unit, was chemically synthesised, and the crystal
structure of the RBP/TriS complex was determined.
This provided unprecedented structural details of
RBP/receptor site-specific binding. The complete
hexasaccharide repeating unit was modelled and
found to aptly fit the extended binding site. The speci-
ficity observed in in vivo phage adhesion assays could
be interpreted in view of the reported structure. There-
fore, by combining synthetic carbohydrate chemistry,
X-ray crystallography and phage plaquing assays, we
suggest that phage adsorption results from distinct
recognition of the RBP towards the core TriS or the
remaining residues of the hexasacchride receptor.
This study provides a novel insight into the adsorption
process of phages targeting saccharides as their
receptors.
Introduction
The infection process of viruses is initiated by intermolecu-
lar interactions between the viral host recognition device
and a receptor usually located at the surface of the host
cell. This receptor can be a protein, a polysaccharide or
both. For example, using reversible attachment to cell wall
saccharides, bacterial viruses (bacteriophages or phages)
can scout the host cell surface to locate and irreversibly
bind to a specific receptor (Parent et al., 2014). Typical
examples include phage T5 (Plancon et al., 2002), which
infects Gram-negative Escherichia coli, and phage SPP1
(Alonso et al., 2006), which infects Gram-positive Bacillus
subtilis. Phage T5 uses the FhuA porin, an iro.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
Follow us on: Pinterest
Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
Genome-scale in silico atpE gene knockout in Escherichia coli could drive novel biological discovery
1. Correspondence To: Bashir Sajo Mienda, Bioinformatics Research Group (BIRG), Department of Biosciences and
Health Sciences, Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, 81310 Skudai
Johor Bahru.Malaysia.
Bioscience and Bioengineering Communications
Journal Homepage: www.bioscibioeng.com
Research Article
Genome-scale in silico atpE gene knockout in Escherichia coli could drive
novel biological discovery
Bashir Sajo Mienda
Bioinformatics Research Group (BIRG), Department of Biosciences and Health Sciences, Faculty of Biosciences
and Medical Engineering, Universiti Teknologi Malaysia, 81310 Skudai Johor Bahru, Malaysia
Received: 23 May 2016; Received in Revised form: 15 July 2016; Accepted: 16 July 2016
Available online: 20 July 2016
Abstract
One of the applications of E. coli genome-scale model is in the biological discovery of underground metabolic
functions of partially characterized genes and/or enzymes. Here we report for the first time, a failed prediction of
atpE gene knockout of no growth in the most recent E. coli reconstruction iJ01366 model, and a positive
experimental growth on glucose, enabling a model-driven biological discovery of the underground metabolic
function of this gene in E. coli metabolism. These findings unfolded what could be described as either scope gaps in
the reconstruction or true biological gaps (knowledge gaps) on the missing atpE gene function in E. coli metabolism.
This study informs other studies that the gaps could be pursued into the E. coli metabolism, leading to a model-
driven discovery in the future. This can be achieved by using gap filling algorithms (such as GrowMatch, SMILEY
and OMNI) in combination with 13
C labeling experiments and/or high throughput tools (such as phenotypic
microarrays and robotic instruments) to update and uncover the missing atpE gene functions under different genetic
and/or environmental conditions.
Keywords: E. coli, genome-scale model, ATP synthase, gene knockout prediction, knowledge gaps, biological
discovery
1. Introduction
Genome-scale science has received remarkable
attention in recent years because of the increasing
development of Genome-scale Metabolic Models
(GEMs). The assembled genome sequences and
plethora of biochemical data in the form of an
integrated biochemical reaction network (Reactome)
of a microbial cell are called GEM (Monk and
Palsson 2014). These models have proven
applications in metabolic engineering, model-driven
discovery (Guzman et al. 2015), prediction of cellular
phenotype, studies of evolutionary process, and
models of interspecies interactions (McCloskey et al.
2013). Model-driven discovery application of GEM
is of particular interest to genome-scale scientists,
because it is used to explore a particular situation of
models’ failure of prediction.
Microbial model predictions are classified into
four (4) computational prediction outcomes: (i) true
positive, (ii) true negative, (iii) false positive and (iv)
false negative predictions. The true positive
prediction occurs when the model prediction of
growth is consistent with the experimental
measurement, and the true negative prediction occurs
when the model prediction of no growth agrees (not
agreed) with the experimental measurement of no
growth (McCloskey et al. 2013; Monk and Palsson
2014). In contrast, predictions of growth and
Biosci Bioeng Commun 2016; 2(2): 112-117
eISSN 2414-1453
2. Genome-scale in silico atpE gene knockout in E. coli
Biosci Bioeng Commun 2(2):112-117 | eISSN:2414-2453 www.bioscibioeng.com 113
experimental measurement of no growth is known as
a false positive outcome, while false negative
prediction occurs when a GEM shows no growth
outcome, but the experimental measurement results
in growth (Monk and Palsson 2014; O'Brien et al.
2015).
Escherichia coli GEM has been used for
biological discovery following a failure in prediction
of gene essentiality, where multiple numbers of genes
knockout reveal hidden reactions in central
metabolism (Kenji et al. 2009). Guided by GEM
outcomes of false negative predictions, Kenji and
colleagues (Kenji et al. 2009) employed gap filling
methods combined with systematic genes knockout in
E. coli central carbon metabolism, that lead to the
discovery of novel metabolic functions of the classic
glycolytic enzymes phosphofructokinase and
aldolase. In addition, the investigators performed
metabolomics analysis that identified a new
metabolite, sedoheptalose-1,7-bisphosphate, that had
not been previously characterized (Kenji et al. 2009).
In a more recent study reported by Palsson and
colleagues (Guzman et al. 2015), they used a top-
down model-driven approach and in vivo
experimentation, where they examined three cases of
genes that were inaccurately predicted as essential.
These genes were evaluated separately and their
isozyme’s functions were discovered, reporting novel
biological insight of their physiological role and
underground metabolic functions in E. coli
metabolism (Guzman et al. 2015).
For the first time, the discrepancies between
GEM predicted and observed growth states of atpE
gene knockout in E. coli are being reported. In this
study, we discovered the existence of what could be
described as scope gaps and/or true biological gaps in
the E. coli iJO1366 reconstruction. The current work
also suggested gap-filling algorithms (such as
GrowMatch, SMILEY and OMNI) that could help
compute the possible reasons for the failure of this
prediction, and possibly design targeted experiments
that could correct inconsistencies in metabolic
knowledge in the future.
2. Materials and methods
2.1. In silico analysis of gene knockout
E. coli genome-scale model iJO1366 (Orth et al.
2011) was employed for the in silico evaluation of
gene deletion by using the Minimization of Metabolic
Adjustment (MOMA) algorithm (Segre et al. 2002)
with the OptFlux software platform-
(http://www.optflux.org) (Rocha et al. 2010). E.
coli iJO1366 model has been tested and proven to be
of use in prediction of computations of growth rates
and metabolite excretion rates from a range of
substrates and genetic conditions (Feist et al. 2010;
Orth et al. 2011). MOMA was described as a flux-
based analysis technique that uses quadratic
programming to search for the nearest point in the
feasible solution space of the mutant model in
relations to its wild-type optimal point feasible
solution space (Segre et al. 2002). The OptFlux
software platform is an imetabolic engineering (ME)
platform that was implemented using the Java
programming, which contains MOMA as a
simulation algorithm. Flux Balance Analysis (FBA)
was used for all phenotype simulations in this study.
All the simulations of the mutant and the wild-type
models were performed using the OptFlux software
version 3.07.
Glucose was chosen as solitary carbon sources
under aerobic conditions. The substrate uptake rates
were constrained to a maximum of 18.5 mmol
gDW‒1
h ‒1
, whereas its corresponding oxygen uptake
rate was set to 20 mmol gDW‒1
h‒1
, because the
environmental condition is aerobic. These values
were selected based on closely established
experimental observations on aerobic and anaerobic
growth in E. coli (Amit Varma 1993; Varma and
Palsson 1994).
2.2. Bacteria and plasmid
E. coli JM109 (F¢ (traD36, proAB+ lacIq, D (lacZ)
M15) endA1 recA1 hsdR17 (rk-, mk +) mcrA supE44
l- gyrA96 relA1 D (lacproAB) thi-1) was used for the
maintenance of pKD4 template plasmid, pKD46
plasmid and the λ-Red helper plasmid. The plasmids
were used strictly following the method described by
Wanner and colleagues. The plasmid pKD4 was
extracted from JM109 using the QIAprep Miniprep
kit (QIAGEN) according to manufacturer’s
specifications.
2.3. Media chemicals and other reagents
E. coli cells used in this study were grown in LB
medium containing 0.5% yeast extract (Difco), 0.5
NaCl and 1% Bacto tryptone (Difco) without or with
antibiotics at the concentrations of 100 µg/ml
ampicillin and 30 µg/ml of Kanamycin. L-arabinose,
glucose were from Sigma Aldrich. KAPA HiFi
Hotstart Ready Mix (2X) was obtained from KAPA
BIOSYSTEMS. Agarose was purchased from Sigma
Aldrich.
3. Genome-scale in silico atpE gene knockout in E. coli
Biosci Bioeng Commun 2(2):112-117 | eISSN:2414-2453 www.bioscibioeng.com 114
Table 1 Sources and characteristics of strains, plasmids and primers used in this study
E. coli strains Relevant characteristics Sources
JM109 Wild-type Lab collection
ΔatpE/b3737 ΔatpE :: FRT-Kan-FRT This study
Plasmids
pKD4 bla FRT-kan-FRT Datsenko and Wanner (2000)
pKD46 bla γ β exo (Red recombinase), temperature-conditional replicon Datsenko and Wanner (2000)
Primers
atpE_F 5’- CTACGCGACA GCGAACATCA CGTACAGACCCAGACCGTGTAGGCTGGAGCTGCTTC-3’
atpE_R 5’- ATGGAAAACCTGAATATGGATCTGCTGTACATGGCTCATATGAATATCCTCCTTAG -3’
2.4. PCR Primers
E. coli gene sequence was used to design forward and
reverse primers with the pKD4 template plasmid
sequence. The primers had a 36-nt 5’ extension
including the gene initiation codon (H1) and 20-nt
sequence (p1) as described previously (Baba et al. 2006;
Datsenko and Wanner 2000). See Table 1 for details of
the primers used in this study.
2.5. Generation of PCR fragments
PCR reactions were carried out in an Eppendorf thermo
cycle using 25 µl reactions containing 12.5 µl of KAPA
HiFi Hotstart Ready Mix (2X), 1µl of pKD4 template
DNA, 1.0 µl of each primer. Reactions were performed
for 30 cycles: 95ºC for 3 min, 98 ͦ C for 20 sec, 55 ͦ C for
15 sec, 72 ͦ C for 1:30 sec, 72 ͦ C for 60 sec and were
cooled at 4 ͦ C. PCR products were purified using the SV
gel and PCR clean up system (Promega, USA),
according to the manufacturer’s protocol. PCR products
were analyzed by 1% agarose gel-electrophoresis using
1X Tris-acetate buffer.
2.6. Electroporation and mutant selection
E. coli JM109 harboring the λ-Red helper plasmid
pKD46 was grown in 100 ml of LB medium with
ampicillin and 1mM L-Arabinose at 30 ͦ C until an
optical density at 600 reached 0.3. Competent cells for
electroporation were prepared as described previously
(Sharan et al. 2009). Then 1 µl (400 ng) of the PCR
fragment was mixed with 50 µl of competent cell in an
ice-cold Eppendorf electroporation cuvette (0.2 cm).
Electroporation was performed at 2.5KV with 2mF and
600Ω, followed by immediate addition of 1ml of SOC
medium which contained (0.5% yeast extract (Difco),
2% Bacto tryptone (Difco), 2.5 mM KCl, 10 mM NaCl,
10 mM MgCl2, 10 mM MgSO4, 20 mM glucose) with 1
mM L-arabinose. The SOC medium mixed with the
electroporated cells was incubated for 2 hours at 37ͦ C.
Selection of kanR
transformant was followed
immediately by spreading a one-tenth portion of it onto
kanamycin agar plate as described by Baba and
colleagues (Baba et al. 2006). Growth tests of the E.
coli mutant strain and the wild-type were performed in
LB medium as described by Baba and colleagues (Baba
et al. 2006).
3. Results and discussions
E. coli genome scale metabolic models have been
established to predict biological capabilities of genes
knockout with notable application in systems metabolic
engineering (Feist et al. 2010; Guzman et al. 2015;
O'Brien et al. 2015; Oberhardt et al. 2009).However,
sometimes models are often characterized by prediction
failures, though it does not sound good if models fail to
predict accurately. These predictive failures are perhaps
of more interest to genome-scale scientists than their
successes, because they represent opportunities for
novel biological discoveries (Guzman et al. 2015; Monk
and Palsson 2014; O'Brien et al. 2015). In this study, we
report for the first time how gene knockout was
predicted to be essential in the model iJO1366 and the
experimental results prove otherwise.
The results of our in silico prediction using E. coli
iJO1366 wild type model under aerobic conditions
indicated a true positive simulation outcome of growth-
growth (GG) consistency (Fig 1 and Fig 2A). On the
other hand, gene knockout result in mutant iJO1366
model under aerobic conditions indicated no growth
(Fig 1), while in the actual experimental measurement,
there is a growth (Fig 2B). This result indicated that
there is a “no growth-growth inconsistency” (NGG)
(Orth and Palsson 2010). This type of prediction
outcome is called false-negative prediction (Monk and
4. Genome-scale in silico atpE gene knockout in E. coli
Biosci Bioeng Commun 2(2):112-117 | eISSN:2414-2453 www.bioscibioeng.com 115
Palsson 2014). This discrepancy indicated that the
reconstructed reactome of the iJO1366 model is
incomplete, representing either scope gaps in the
reconstruction or true biological gaps (knowledge gaps).
The scope gaps sometimes exist in a reconstruction,
because large scale metabolic network models do not
entail other systems such as signaling, transcription and
translation, as such, metabolites produced during
metabolism and enter these other systems could be left
as gaps in the models, despite the fact that their
biological functions are fully specified (Orth and
Palsson 2010). The true biological gaps on the other
hand, represent cases of existing unknown biochemical
reactions that produce or consume certain metabolites,
which in turn, show a gap that could not be realized
using a reconstruction (Orth and Palsson 2010). These
type of gaps represent our limited knowledge, and to fill
them, new biological discoveries must be pursued,
combining gap filling algorithms, such as GrowMatch
(Kumar and Maranas 2009), SMILEY (Reed et al.
2006) and OMNI (Herrga et al. 2006) with experimental
verifications using 13
C labeling experiments and/or high
throughput tools such as phenotypic microarrays and
robotic instruments to screen cells at high rates
(O'Brien et al. 2015).
Fig 1 In silico growth rates of the wild-type (iJO1366
model) and the mutant Model (ΔatpE).
Genome-scale Metabolic Models (GEM) have
been established to accurately predict metabolic
engineering interventions (Feist et al. 2010; McCloskey
et al. 2013; Oberhardt et al. 2009; Orth et al. 2011),
although the accuracy of the prediction exercise of any
GEM is predicated on an accurate reconstruction of the
reactome (Monk & Palsson, 2014). An incompletely
reconstructed reactome leads to false negative
predictions. Correct predictions usually align with the
experimental results while inaccurate predictions do not
(O'Brien et al. 2015). Prediction failures can be
employed to systematically design strategies using a
number of algorithms (GrowMatch, SMILEY, OMNI
etc.) to build computer-aided hypotheses that could
address these failures. The discrepancies seen in the
current study with the gene knockout could be
addressed by using computer-aided hypotheses building
with gap-filling algorithm(s) and/or employed a
previously established workflow methodology for
model-driven discovery (Guzman et al. 2015) to unfold
the underground metabolic functions of the gene and its
relevant isozyme. Reconciling the differences between
GEM predicted results and observed experimental
growth states has now been considered to be a proven
strategy for novel biological discovery (O'Brien et al.
2015).
Fig 2A Experimental growth profile of the wild-type E.
coli strain.
Fig 2B Experimental growth profile of the atpE mutant
strain.
5. Genome-scale in silico atpE gene knockout in E. coli
Biosci Bioeng Commun 2(2):112-117 | eISSN:2414-2453 www.bioscibioeng.com 116
4. Conclusion
Predictive failures in E. coli GEM are perhaps of more
interest to genome-scale scientists, than success, as it
paves way for biological discovery. The discrepancies
between experimental observations and GEM
predictions have been used to unfold gaps in our
knowledge, where targeted experiments can be designed
to correct inconsistencies in metabolic knowledge. In
this study, we report for the first time, the discrepancies
between GEM predicted and observed growth states of
gene knockout in E. coli, where the existence of what
could be described as scope gaps and/or true biological
gaps in the E. coli iJO1366 reconstruction was
discovered. The current work also suggested the use of
gap-filling algorithms (such as GrowMatch, SMILEY
and OMNI) that could help compute the possible
reasons for the failure of this prediction, and possibly
design targeted experiments that could correct
inconsistencies in metabolic knowledge in the future.
5. Conflict of interest
There is no conflict in interest with authors during the
work accomplishment.
6. References
Amit Varma BWB and Palsson BO (1993)
Stoichiometric Interpretation of Escherichia coli
Glucose Catabolism under Various Oxygenation
Rates. Appl Environ Microbiol; 59(8): 2465-2473.
Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y,
Baba M, et al. (2006) Construction of Escherichia
coli K-12 in-frame, single-gene knockout mutants:
the Keio collection. Mol Syst Biol; 2:2006. 0008.
Datsenko KA and Wanner BL (2000) One-step
inactivation of chromosomal genes in Escherichia
coli K-12 using PCR products. Proc Natl Acad Sci
USA; 97(12), 6640-6645.
Feist AM, Zielinski DC, Orth JD, Schellenberger J,
Herrgard MJ and Palsson BO (2010) Model-driven
evaluation of the production potential for growth-
coupled products of Escherichia coli. Metab Eng;
12(3):173-186.
Guzman GI, Utrilla J, Nurk S, Brunk E, Monk JM,
Ebrahim A, et al. (2015). Model-driven discovery
of underground metabolic functions in Escherichia
coli. Proc Natl Acad Sci USA; 112(3): 929-934.
Herrga MJ, Fong SS and Palsson BØ (2006)
Identification of Genome-Scale Metabolic
Network Models Using Experimentally Measured
Flux Profiles. Plos Computational Biology; 2(7),
676-686.
Kenji N, Yoshihiro T, Nobuyoshi I, Tomoyoshi S, Miki
H, Hisami W, et al. (2009) Systematic phenome
analysis of Escherichia coli multiple-knockout
mutants reveals hidden reactions in central carbon
metabolism. Mol Syst Biol; 5(306): 1-14.
Kumar VS and Maranas CD (2009). GrowMatch: An
Automated Method for Reconciling /In Vivo
Growth Predictions. Plos Computational Biology;
5(3):1-13.
McCloskey D, Palsson BO and Feist AM (2013) Basic
and applied uses of genome-scale metabolic
network reconstructions of Escherichia coli. Mol
Syst Biol; 9: 661.
Monk J and Palsson BO (2014) Genetics. Predicting
microbial growth. Science; 344(6191): 1448-1449.
O'Brien EJ, Monk J M and Palsson BO (2015) Using
Genome-scale Models to Predict Biological
Capabilities. Cell; 161(5): 971-987.
Oberhardt MA, Palsson BO and Papin JA (2009).
Applications of genome-scale metabolic
reconstructions. Mol Syst Biol; 5: 320.
Orth JD, Conrad TM, Na J, Lerman JA, Nam H, Feist
AM and Palsson BO (2011) A comprehensive
genome-scale reconstruction of Escherichia coli
metabolism--2011. Mol Syst Biol; 7: 535.
Orth JD and Palsson BO (2010) Systematizing the
generation of missing metabolic knowledge.
Biotechnol Bioeng; 107(3); 403-412.
Reed JL, Patel TR, Chen KH, Joyce AR, Applebee MK,
Herring CD, et al. (2006) Systems approach to
refining genome annotation. Proc Natl Acad Sci
USA; 103(46): 17480-17484.
Rocha I, Maia P, Evangelista P, et al. (2010). OptFlux:
an open-source software platform for in silico
metabolic engineering. BMC Syst Biol; 4: 45.
Segre D, Vitkup D and Church GM (2002). Analysis of
optimality in natural and perturbed metabolic
networks. Proc Natl Acad Sci USA; 99(23):
15112-15117.
Sharan SK, Thomason LC, Kuznetsov SG and Court DL
(2009) Recombineering: a homologous
recombination-based method of genetic
engineering. Nat Protoc; 4(2): 206-223.
Varma A and Palsson BO (1994) Stoichiometric Flux
Balance Models Quantitatively Predict Growth and
Metabolic By-Product Secretion in Wild-Type
Escherichia coli W3110. Appl Environ. Microbiol;
60: 3724 - 3731.
.
6. Genome-scale in silico atpE gene knockout in E. coli
Biosci Bioeng Commun 2(2):112-117 | eISSN:2414-2453 www.bioscibioeng.com 117
Under the terms of the Creative Commons Attribution-Noncommercial 4.0 International License.
How to cite this article: Mienda BS (2016) Genome-scale in silico atpE gene knockout in Escherichia coli
could drive novel biological discovery. Biosci Bioeng Commun; 2 (2): 112-117.