Immunoinformatics-Driven Strategies for Advancing Epitope-Based Vaccine Design for West Nile Virus.

The West Nile virus (WNV) is the causative agent of West Nile disease (WND), which poses a potential risk of meningitis or encephalitis. The aim of the study was to design an epitope-based vaccine for WNV by utilizing computational analyses. The epitope-based vaccine design process encompassed WNV sequence collection, phylogenetic tree construction, and sequence alignment. Computational models identified B-cell and T-cell epitopes, followed by immunological property analysis. Epitopes were then modeled and docked with B-cell receptors, MHC I, and MHC II. Molecular dynamics simulations further explored dynamic interactions between epitopes and receptors. The findings indicated that the B-cell epitope QINHHWHKSGSSIG, along with three T-cell epitopes (FLVHREWFM for MHC I, NPFVSVATANAKVLI for MHC II, and NAYYVMTVGTKTFLV for MHC II), successfully passed the immunological evaluations. These four epitopes were further subjected to docking and molecular dynamics simulation studies. Although each demonstrated favorable affinities with their respective receptors, only NAYYVMTVGTKTFLV displayed a stable interaction with MHC II during MDS analysis, hence emerging as a potential candidate for a WNV epitope-based vaccine. This study demonstrates a comprehensive approach to epitope vaccine design, combining computational analyses, molecular modeling, and simulation techniques to identify potential vaccine candidates for WNV.

Epigenetic Targets and Pathways Linked to SARS-CoV-2 Infection and Pathology.

The scale at which the SARS-CoV-2/COVID-19 pandemic has spread remains enormous. Provided the genetic makeup of the virus and humans is readily available, the quest for knowing the mechanism and epidemiology continues to prevail across the entire scientific community. Several aspects, including immunology, molecular biology, and host-pathogen interaction, are continuously being dug into for preparing the human race for future pandemics. The exact reasons for vast differences in symptoms, pathophysiological implications of COVID-infections, and mortality differences remain elusive. Hence, researchers are also looking beyond traditional genomics, proteomics, and transcriptomics approach, especially entrusting the environmental regulation of the genetic landscape of COVID-human interactions. In line with these questions lies a critical process called epigenetics. The epigenetic perturbations in both host and parasites are a matter of great interest to unravel the disparities in COVID-19 mortalities and pathology. This review provides a deeper insight into current research on the epigenetic landscape of SARS-CoV-2 infection in humans and potential targets for augmenting the ongoing investigation. It also explores the potential targets, pathways, and networks associated with the epigenetic regulation of processes involved in SARS-CoV-2 pathology.

Application of CRISPR/Cas9 Technology in Cancer Treatment: A Future Direction.

Gene editing, especially with clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR-Cas9), has advanced gene function science. Gene editing's rapid advancement has increased its medical/clinical value. Due to its great specificity and efficiency, CRISPR/Cas9 can accurately and swiftly screen the whole genome. This simplifies disease-specific gene therapy. To study tumor origins, development, and metastasis, CRISPR/Cas9 can change genomes. In recent years, tumor treatment research has increasingly employed this method. CRISPR/Cas9 can treat cancer by removing genes or correcting mutations. Numerous preliminary tumor treatment studies have been conducted in relevant fields. CRISPR/Cas9 may treat gene-level tumors. CRISPR/Cas9-based personalized and targeted medicines may shape tumor treatment. This review examines CRISPR/Cas9 for tumor therapy research, which will be helpful in providing references for future studies on the pathogenesis of malignancy and its treatment.

Recent Trends and Developments in Multifunctional Nanoparticles for Cancer Theranostics.

Conventional anticancer treatments, such as radiotherapy and chemotherapy, have significantly improved cancer therapy. Nevertheless, the existing traditional anticancer treatments have been reported to cause serious side effects and resistance to cancer and even to severely affect the quality of life of cancer survivors, which indicates the utmost urgency to develop effective and safe anticancer treatments. As the primary focus of cancer nanotheranostics, nanomaterials with unique surface chemistry and shape have been investigated for integrating cancer diagnostics with treatment techniques, including guiding a prompt diagnosis, precise imaging, treatment with an effective dose, and real-time supervision of therapeutic efficacy. Several theranostic nanosystems have been explored for cancer diagnosis and treatment in the past decade. However, metal-based nanotheranostics continue to be the most common types of nonentities. Consequently, the present review covers the physical characteristics of effective metallic, functionalized, and hybrid nanotheranostic systems. The scope of coverage also includes the clinical advantages and limitations of cancer nanotheranostics. In light of these viewpoints, future research directions exploring the robustness and clinical viability of cancer nanotheranostics through various strategies to enhance the biocompatibility of theranostic nanoparticles are summarised.

Artificial Intelligence for Clinical Diagnosis and Treatment of Prostate Cancer.

As medical science and technology progress towards the era of "big data", a multi-dimensional dataset pertaining to medical diagnosis and treatment is becoming accessible for mathematical modelling. However, these datasets are frequently inconsistent, noisy, and often characterized by a significant degree of redundancy. Thus, extensive data processing is widely advised to clean the dataset before feeding it into the mathematical model. In this context, Artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL) algorithms based on artificial neural networks (ANNs) and their types, are being used to produce a precise and cross-sectional illustration of clinical data. For prostate cancer patients, datasets derived from the prostate-specific antigen (PSA), MRI-guided biopsies, genetic biomarkers, and the Gleason grading are primarily used for diagnosis, risk stratification, and patient monitoring. However, recording diagnoses and further stratifying risks based on such diagnostic data frequently involves much subjectivity. Thus, implementing an AI algorithm on a PC's diagnostic data can reduce the subjectivity of the process and assist in decision making. In addition, AI is used to cut down the processing time and help with early detection, which provides a superior outcome in critical cases of prostate cancer. Furthermore, this also facilitates offering the service at a lower cost by reducing the amount of human labor. Herein, the prime objective of this review is to provide a deep analysis encompassing the existing AI algorithms that are being deployed in the field of prostate cancer (PC) for diagnosis and treatment. Based on the available literature, AI-powered technology has the potential for extensive growth and penetration in PC diagnosis and treatment to ease and expedite the existing medical process.

Systematic Review on Pathophysiological Complications in Severe COVID-19 among the Non-Vaccinated and Vaccinated Population.

COVID-19, caused by SARS-CoV-2, is one of the longest viral pandemics in the history of mankind, which have caused millions of deaths globally and induced severe deformities in the survivals. For instance, fibrosis and cavities in the infected lungs of COVID-19 are some of the complications observed in infected patients post COVID-19 recovery. These health abnormalities, including is multiple organ failure-the most striking pathological features of COVID-19-have been linked with diverse distribution of ACE2 receptor. Additionally, several health complications reports were reported after administration of COVID-19 vaccines in healthy individuals, but clinical or molecular pathways causing such complications are not yet studied in detail. Thus, the present systematic review established the comparison of health complication noted in vaccinated and non-vaccinated individuals (COVID-19 infected patients) to identify the association between vaccination and the multiorgan failure based on the data obtained from case studies, research articles, clinical trials/Cohort based studies and review articles published between 2020-2022. This review also includes the biological rationale behind the COVID-19 infection and its subsequent symptoms and effects including multiorgan failure. In addition, multisystem inflammatory syndrome (MIS) has been informed in individuals post vaccination that resulted in multiorgan failure but, no direct correlation of vaccination with MIS has been established. Similarly, hemophagocytic lymphohistiocytosis (HLH) also noted to cause multiorgan failure in some individuals following full vaccination. Furthermore, severe complications were recorded in elderly patients (+40 years of age), indicates that older age individuals are higher risk by COVID-19 and post vaccination, but available literature is not sufficient to comply with any conclusive statements on relationship between vaccination and multiorgan failure.

Evaluation of Bi-Lateral Co-Infections and Antibiotic Resistance Rates among COVID-19 Patients in Lahore, Pakistan.

Background and Objective: Bacterial infections are among the major complications of many viral respiratory tract illnesses, such as influenza and coronavirus disease-2019 (COVID-19). These bacterial co-infections are associated with an increase in morbidity and mortality rates. The current observational study was conducted at a tertiary care hospital in Lahore, Pakistan among COVID-19 patients with the status of oxygen dependency to see the prevalence of bacterial co-infections and their antibiotic susceptibility patterns. Materials and Methods: A total of 1251 clinical samples were collected from already diagnosed COVID-19 patients and tested for bacterial identification (cultures) and susceptibility testing (disk diffusion and minimum inhibitory concentration) using gold standard diagnostic methods. Results: From the total collected samples, 234 were found positive for different bacterial isolates. The most common isolated bacteria were Escherichia coli (E. coli) (n = 62) and Acinetobacter baumannii (A. baumannii) (n = 47). The E. coli isolates have shown the highest resistance to amoxicillin and ampicillin, while in the case of A. baumannii, the highest resistance was noted against tetracycline. The prevalence of methicillin resistant Staphylococcus aureus (MRSA) was 14.9%, carbapenem resistant Enterobacteriaceae (CRE) was 4.5%, and vancomycin resistant Enterococcus (VRE) was 3.96%. Conclusions: The results of the current study conclude that empiric antimicrobial treatment in critically ill COVID-19 patients may be considered if properly managed within institutional or national level antibiotic stewardship programs, because it may play a protective role in the case of bacterial co-infections, especially when a patient has other AMR risk factors, such as hospital admission within the previous six months.

Execution and Design of an Anti HPIV-1 Vaccine with Multiple Epitopes Triggering Innate and Adaptive Immune Responses: An Immunoinformatic Approach.

Human Parainfluenza Virus (HPIV) Type-1, which is an anti-sense ribonucleic acid (RNA) virus belonging to the paramyxoviridae family, induces upper and lower respiratory tract infections. The infections caused by the HPIV Type-1 virus are usually confined to northwestern regions of America. HPIV-1 causes infections through the virulence of the hemagglutinin-neuraminidase (HN) protein, which plays a key role in the attachment of the viral particle with the host's receptor cells. To the best of our knowledge, there is no effective antiviral drugs or vaccines being developed to combat the infection caused by HPIV-1. In the current study, a multiple epitope-based vaccine was designed against HPIV-1 by taking the viral HN protein as a probable vaccine candidate. The multiple epitopes were selected in accordance with their allergenicity, antigenicity and toxicity scoring. The determined epitopes of the HN protein were connected simultaneously using specific conjugates along with an adjuvant to construct the subunit vaccine, with an antigenicity score of 0.6406. The constructed vaccine model was docked with various Toll-like Receptors (TLRs) and was computationally cloned in a pET28a (+) vector to analyze the expression of vaccine sequence in the biological system. Immune stimulations carried out by the C-ImmSim Server showed an excellent result of the body's defense system against the constructed vaccine model. The AllerTop tool predicted that the construct was non-allergen with and without the adjuvant sequence, and the VaxiJen 2.0 with 0.4 threshold predicted that the construct was antigenic, while the Toxinpred predicted that the construct was non-toxic. Protparam results showed that the selected protein was stable with 36.48 instability index (II) scores. The Grand average of Hydropathicity or GRAVY score indicated that the constructed protein was hydrophilic in nature. Aliphatic index values (93.53) confirmed that the construct was thermostable. This integrated computational approach shows that the constructed vaccine model has a potential to combat laryngotracheobronchitis infections caused by HPIV-I.

Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates.

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI's applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor's prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.

Formulation and Characterization of Chitosan-Decorated Multiple Nanoemulsion for Topical Delivery In Vitro and Ex Vivo.

In the present study, chitosan-decorated multiple nanoemulsion (MNE) was formulated using a two-step emulsification process. The formulated multiple nanoemuslion was evaluated physiochemically for its size and zeta potential, surface morphology, creaming and cracking, viscosity and pH. A Franz diffusion cell apparatus was used to carry out in vitro drug-release and permeation studies. The formulated nanoemulsion showed uniform droplet size and zeta potential. The pH and viscosity of the formulated emulsion were in the range of and suitable for topical delivery. The drug contents of the simple nanoemulsion (SNE), the chitosan-decorated nanoemulsion (CNE) and the MNE were 71 ± 2%, 82 ± 2% and 90 ± 2%, respectively. The formulated MNE showed controlled release of itraconazole as compared with that of the SNE and CNE. This was attributed to the chitosan decoration as well as to formulating multiple emulsions. The significant permeation and skin drug retention profile of the MNE were attributed to using the surfactants tween 80 and span 20 and the co-surfactant PEG 400. ATR-FTIR analysis confirmed that the MNE mainly affects the lipids and proteins of the skin, particularly the stratum corneum, which results in significantly higher permeation and retention of the drug. It was concluded that the proposed MNE formulation delivers drug to the target site of the skin and can be therapeutically used for various cutaneous fungal infections.

In Silico Analysis Identified Putative Pathogenic Missense nsSNPs in Human SLITRK1 Gene.

Human DNA contains several variations, which can affect the structure and normal functioning of a protein. These variations could be single nucleotide polymorphisms (SNPs) or insertion-deletions (InDels). SNPs, as opposed to InDels, are more commonly present in DNA and may cause genetic disorders. In the current study, several bioinformatic tools were used to prioritize the pathogenic variants in the SLITRK1 gene. Out of all of the variants, 16 were commonly predicted to be pathogenic by these tools. All the variants had very low frequency, i.e., <0.0001 in the global population. The secondary structure of all filtered variants was predicted, but no structural change was observed at the site of variation in any variant. Protein stability analysis of these variants was then performed, which determined a decrease in protein stability of 10 of the variants. Amino acid conservation analysis revealed that all the amino acids were highly conserved, indicating their structural and functional importance. Protein 3D structure of wildtype SLITRK1 and all of its variants was predicted using I-TASSER, and the effect of variation on 3D structure of the protein was observed using the Missense3D tool, which presented the probable structural loss in three variants, i.e., Asn529Lys, Leu496Pro and Leu94Phe. The wildtype SLITRK1 protein and these three variants were independently docked with their close interactor protein PTPRD, and remarkable differences were observed in the docking sites of normal and variants, which will ultimately affect the functional activity of the SLITRK1 protein. Previous studies have shown that mutations in SLITRK1 are involved in Tourette syndrome. The present study may assist a molecular geneticist in interpreting the variant pathogenicity in research as well as diagnostic setup.

In Silico Analysis of the L-2-Hydroxyglutarate Dehydrogenase Gene Mutations and Their Biological Impact on Disease Etiology.

The L-2-hydroxyglutarate dehydrogenase (L2HGDH) gene encodes an important mitochondrial enzyme. However, its altered activity results in excessive levels of L-2-hydroxyglutarate, which results in diverse psychiatric features of intellectual disability. In the current study, we executed an in-silico analysis of all reported L2HGDH missense and nonsense variants in order to investigate their biological significance. Among the superimposed 3D models, the highest similarity index for a wild-type structure was shown by the mutant Glu336Lys (87.26%), while the lowest similarity index value was shown by Arg70* (10.00%). Three large active site pockets were determined using protein active site prediction, in which the 2nd largest pocket was shown to encompass the substrate L-2-hydroxyglutarate (L2HG) binding residues, i.e., 89Gln, 195Tyr, 402Ala, 403Gly and 404Val. Moreover, interactions of wild-type and mutant L2HGDH variants with the close functional interactor D2HGDH protein resulted in alterations in the position, number and nature of networking residues. We observed that the binding of L2HG with the L2HGDH enzyme is affected by the nature of the amino acid substitution, as well as the number and nature of bonds between the substrate and protein molecule, which are able to affect its biological activity.

Formulation and Evaluation of Hydrophilic Polymer Based Methotrexate Patches: In Vitro and In Vivo Characterization.

This study attempted to develop and evaluate controlled-release matrix-type transdermal patches with different ratios of hydrophilic polymers (sodium carboxymethylcellulose and hydroxypropyl methylcellulose) for the local delivery of methotrexate. Transdermal patches were formulated by employing a solvent casting technique using blends of sodium carboxymethylcellulose (CMC-Na) and hydroxypropylmethylcellulose (HPMC) polymers as rate-controlling agents. The F1 formulated patch served as the control formulation with a 1:1 polymer concentration. The F9 formulation served as our optimized formulation due to suitable physicochemical properties yielded through the combination of CMC-Na and HPMC (5:1). Drug excipient compatibilities (ATR-FTIR) were performed as a preformulation study. The ATR-FTIR study depicted great compatibility between the drug and the polymers. Physicochemical parameters, kinetic modeling, in vitro drug release, ex vivo drug permeation, skin drug retention, and in vivo studies were also carried out for the formulated patches. The formulated patches exhibited a clear, smooth, elastic nature with good weight uniformity, % moisture uptake, drug content, and thickness. Physicochemical characterization revealed folding endurance ranging from 62 ± 2.21 to 78 ± 1.54, tensile strength from 9.42 ± 0.52 to 12.32 ± 0.72, % swelling index from 37.16 ± 0.17 to 76.24 ± 1.37, and % drug content from 93.57 ± 5.34 to 98.19 ± 1.56. An increase in the concentration of the CMC-Na polymer (F9) resulted in increased drug release from the formulated transdermal patches. Similarly, drug permeation and retention were found to be higher in the F9 formulation compared to the other formulations (F1-F8). A drug retention analysis revealed that the F9 formulation exhibited 13.43% drug retention in the deep layers of the skin compared to other formulations (F1-F8). The stability study indicated that, during the study period of 60 days, no significant changes in the drug content and physical characteristics were found. ATR-FTIR analysis of rabbit skin samples treated with the formulated transdermal patches revealed that hydrophilic polymers mainly affect the skin proteins (ceramide and keratins). A pharmacokinetic profile revealed Cmax was 1.77.38 ng/mL, Tmax was 12 h, and t1/2 was 17.3 ± 2.21. In vivo studies showed that the skin drug retention of F9 was higher compared to the drug solution. These findings reinforce that methotrexate-based patches can possibly be used for the management of psoriasis. This study can reasonably conclude that methotrexate transdermal matrix-type patches with CMC-Na and HPMC polymers at different concentrations effectively sustain drug release with prime permeation profiles and better bioavailability. Therefore, these formulated patches can be employed for the potential management of topical diseases, such as psoriasis.

Tacrolimus-Loaded Solid Lipid Nanoparticle Gel: Formulation Development and In Vitro Assessment for Topical Applications.

The currently available topical formulations of tacrolimus have minimal and variable absorption, elevated mean disposition half-life, and skin irritation effects resulting in patient noncompliance. In our study, we fabricated tacrolimus-loaded solid lipid nanoparticles (SLNs) that were converted into a gel for improved topical applications. The SLNs were prepared using a solvent evaporation method and characterized for their physicochemical properties. The particle size of the SLNs was in the range of 439 nm to 669 nm with a PDI of ≤0.4, indicating a monodispersed system. The Zeta potential of uncoated SLNs (F1-F5) ranged from -25.80 to -15.40 mV. Those values reverted to positive values for chitosan-decorated formulation (F6). The drug content and entrapment efficiency ranged between 0.86 ± 0.03 and 0.91 ± 0.03 mg/mL and 68.95 ± 0.03 and 83.68 ± 0.04%, respectively. The pH values of 5.45 to 5.53 depict their compatibility for skin application. The surface tension of the SLNs decreased with increasing surfactant concentration that could increase the adherence of the SLNs to the skin. The release of drug from gel formulations was significantly retarded in comparison to their corresponding SLN counterparts (p ≤ 0.05). Both SLNs and their corresponding gel achieved the same level of drug permeation, but the retention of the drug was significantly improved with the conversion of SLNs into their corresponding gel formulation (p ≤ 0.05) due to its higher bioadhesive properties.

Krüppel-Like Transcription Factor KLF1 Is Required for Optimal γ- and ß-Globin Expression in Human Fetal Erythroblasts.

In human adult erythroid cells, lower than normal levels of Krüppel-like transcription factor 1 (KLF1) are generally associated with decreased adult ß- and increased fetal γ-globin gene expression. KLF1 also regulates BCL11A, a known repressor of adult γ-globin expression. In seeming contrast to the findings in adult cells, lower amounts of KLF1 correlate with both reduced embryonic and reduced fetal ß-like globin mRNA in mouse embryonic erythroid cells. The role of KLF1 in primary human fetal erythroid cells, which express both γ- and ß-globin mRNA, is less well understood. Therefore, we studied the role of KLF1 in ex vivo differentiated CD34+ umbilical cord blood cells (UCB erythroblasts), representing the fetal milieu. In UCB erythroblasts, KLF1 binds to the ß-globin locus control region (LCR), and the ß-globin promoter. There is very little KLF1 binding detectable at the γ-globin promoter. Correspondingly, when cultured fetal UCB erythroblasts are subjected to lentiviral KLF1 knockdown, the active histone mark H3K4me3 and RNA pol II recruitment are diminished at the ß- but not the γ-globin gene. The amount of KLF1 expression strongly positively correlates with ß-globin mRNA and weakly positively correlates with BCL11A mRNA. With modest KLF1 knockdown, mimicking haploinsufficiency, γ-globin mRNA is increased in UCB erythroblasts, as is common in adult cells. However, a threshold level of KLF1 is evidently required, or there is no absolute increase in γ-globin mRNA in UCB erythroblasts. Therefore, the role of KLF1 in γ-globin regulation in fetal erythroblasts is complex, with both positive and negative facets. Furthermore, in UCB erythroblasts, diminished BCL11A is not sufficient to induce γ-globin in the absence of KLF1. These findings have implications for the manipulation of BCL11A and/or KLF1 to induce γ-globin for therapy of the ß-hemoglobinopathies.

Kruppel-like factor 1 (KLF1), KLF2, and Myc control a regulatory network essential for embryonic erythropoiesis.

The Krüppel-like factor 1 (KLF1) and KLF2 positively regulate embryonic ß-globin expression and have additional overlapping roles in embryonic (primitive) erythropoiesis. KLF1(-/-) KLF2(-/-) double knockout mice are anemic at embryonic day 10.5 (E10.5) and die by E11.5, in contrast to single knockouts. To investigate the combined roles of KLF1 and KLF2 in primitive erythropoiesis, expression profiling of E9.5 erythroid cells was performed. A limited number of genes had a significantly decreasing trend of expression in wild-type, KLF1(-/-), and KLF1(-/-) KLF2(-/-) mice. Among these, the gene for Myc (c-Myc) emerged as a central node in the most significant gene network. The expression of the Myc gene is synergistically regulated by KLF1 and KLF2, and both factors bind the Myc promoters. To characterize the role of Myc in primitive erythropoiesis, ablation was performed specifically in mouse embryonic proerythroblast cells. After E9.5, these embryos exhibit an arrest in the normal expansion of circulating red cells and develop anemia, analogous to KLF1(-/-) KLF2(-/-) embryos. In the absence of Myc, circulating erythroid cells do not show the normal increase in α- and ß-like globin gene expression but, interestingly, have accelerated erythroid cell maturation between E9.5 and E11.5. This study reveals a novel regulatory network by which KLF1 and KLF2 regulate Myc to control the primitive erythropoietic program.

Transcription factors KLF1 and KLF2 positively regulate embryonic and fetal beta-globin genes through direct promoter binding.

Krüppel-like factors (KLFs) control cell differentiation and embryonic development. KLF1 (erythroid Krüppel-like factor) plays essential roles in embryonic and adult erythropoiesis. KLF2 is a positive regulator of the mouse and human embryonic ß-globin genes. KLF1 and KLF2 have highly homologous zinc finger DNA-binding domains. They have overlapping roles in embryonic erythropoiesis, as demonstrated using single and double KO mouse models. Ablation of the KLF1 or KLF2 gene causes embryonic lethality, but double KO embryos are more anemic and die sooner than either single KO. In this work, a dual human ß-globin locus transgenic and KLF knockout mouse model was used. The results demonstrate that the human ε- (embryonic) and γ-globin (fetal) genes are positively regulated by KLF1 and KLF2 in embryos. Conditional KO mouse experiments indicate that the effect of KLF2 on embryonic globin gene regulation is at least partly erythroid cell-autonomous. KLF1 and KLF2 bind directly to the promoters of the human ε- and γ-globin genes, the mouse embryonic Ey- and ßh1-globin genes, and also to the ß-globin locus control region, as demonstrated by ChIP assays with mouse embryonic blood cells. H3K9Ac and H3K4me3 marks indicate open chromatin and active transcription, respectively. These marks are diminished at the Ey-, ßh1-, ε- and γ-globin genes and locus control region in KLF1(-/-) embryos, correlating with reduced gene expression. Therefore, KLF1 and KLF2 positively regulate the embryonic and fetal ß-globin genes through direct promoter binding. KLF1 is required for normal histone modifications in the ß-globin locus in mouse embryos.