Patent Application
20230227815
The present inventions describes a Facile Accelerated Specific Therapeutic (FAST) pipeline to rapidly design, built and test therapeutic oligomers (FASTmers) against mammalian or microbial genes of interest.
The encroaching crisis of multidrug-resistant (MDR) pathogens, incited in part by the broad-spectrum activity of many conventional antibiotics and worsened by the dwindling antibiotic pipeline, has led to an increase in research of antisense nucleic acid-based therapies. Antisense antibiotic therapies bind to bacterial nucleic acid molecules in a sequence-specific manner to inhibit the transcription and translation of important or essential genes. The sequence-specificity allows for precise targeting of a single pathogen and allows for therapies that are more adaptive to bacterial mutations than conventional antibiotics. One of the most promising of these antisense antibiotic strategies is peptide nucleic acids (PNA), synthetic peptide-nucleobase hybrids that present a cloning-free antisense strategy. Compared with other antisense strategies, PNA present better thermal stability, and better intracellular stability—PNA is not recognized by bacterial nucleases or proteases—and stronger binding due to a lack of electrostatic repulsion between PNA and nucleic acid backbones. Furthermore, PNA have demonstrated the ability to discriminate single mismatches in short sequences, allowing for a high degree of specificity. PNA have also shown to be an effective antibiotic platform.
Though PNA do offer advantages in stability and specificity, it remains necessary to both screen and experimentally test possible PNA sequences to maximize both of these qualities. However, this requires tedious design processes that involve multiple disjoint alignment programs and stability calculations. As such, there is a need to overcome the limitations in the art and develop a rapid and cost-effective process for the design, synthesis, and testing of PNA antibiotics.
One aspect of the inventive technology includes a novel approach to counter emergent bacterial threats through the development of a Facile Accelerated Specific Therapeutic (FAST) system to design, built and test treatments within a time scale of hours to days against any emergent bacterial pathogen including multi-drug resistant (MDR) bacteria. In a preferred embodiment, the invention includes a the Facile and Accelerated high throughput design of therapeutic oligomers, referred to generally as FASTmers. In certain preferred aspects, a FASTmers may include peptide nucleic acids (PNAs) based antisense therapeutics that can block translation of a desired gene by binding to its mRNA in pathogen-specific manner for targeted inhibition of growth/killing of a desired pathogen. Additional embodiments may further include the automated and high-throughput parallel synthesis of a FASTmer therapeutic library for generation of on-site therapeutic molecules, and development of a bacterial secretion system, such as Type III secretion system, associated on a probiotic delivery system to efficiently provide therapeutic FASTmer molecules to infected host cells to overcome challenges of transport, toxicity, and bioavailability. In this preferred embodiment, the inventive technology may include the testing of one or more designed and built FASTmers in a high-throughput manner, such as in a relevant macrophage based host-infection model.
As detailed below, in one aspect of the invention, a FASTmer, or PNA Finder toolbox may provide a set of functions that allow for rapid identification and screening of potential target gene sequences for peptide nucleic acid antibiotics. The toolbox incorporates the individual tools Get Sequences and Find Off-Targets, which provide automated pipelines of the alignment tools Bowtie 2, SAMTools, and BEDTools that work together with novel Python-based tools. The Get Sequences tool may be used to identify sequences in a given bacterial genome that PNA antibiotics could potentially target, based on a user-provided list of target genes. This tool provides as output a FASTA file of these sequences, a corresponding list of the PNA peptides that may bind to each target sequence, and analysis of these peptides for possible issues related solubility and self-complementarity. In one aspect of the invention, the Get Sequences tool may automate the target gene selection process by providing users with the option to use essential gene databases to identify gene targets in a particular organism. Furthermore, transcription start site prediction may be incorporated into the sequence warnings, in order to screen PNA candidates that are targeted to non-mRNA sequences.
In one aspect of the invention, the Find Off-Targets tool may be used to identify genomic loci that a given FASTmer sequence, and preferably a PNA sequence—or set of sequences—is predicted to bind, whether or not they represent the target locus. The tool provides as an output a BED file of these alignments, a tab-delimited output file of all alignments predicted to inhibit a gene, and a count file with the sum total inhibitory alignments for each FASTmer in the given genome. Additional aspects may incorporate a method for screening FASTmer candidates based on estimates off-targeting within the commensal microbe communities of specific microbiome environments. Still further aspects may add predictions of human off-targeting.
One aspect of the current invention may include the rapid identification and synthesis of FASTmer molecules, and preferably PNA molecules designed to either increase transcription or decrease protein expression of one or more radiation responsive genes. This embodiment may use a FAST platform pipeline to design FASTmer PNA based antisense therapeutics that can block translation of any desired gene by binding to its mRNA in a gene-specific manner.
One aspect of the current invention may include the development a bioinformatics software tool configured to design a catalog of unique FASTmer molecules, and preferably PNA molecules that can target (a) essential genes in pathogenic bacteria, (b) antimicrobial resistance genes, and (c) reduce chances of off-target effect by comparison to other pathogenic bacterial strains, gut microbiome, and human transcriptome. One embodiment may adopt an automated FASTmer synthesis method and a novel micro-bot based FASTmer delivery strategy. In this embodiment, the inventive technology may include systems and methods to synthesize FASTmer s in an automated peptide synthesizer to achieve high-throughput, lower costs, and shorter time scales to generate therapy that can be used to treat patient quickly. Additional embodiments may include the use of a novel probiotic-based transport strategy to deliver the therapeutic FASTmer molecules with higher efficiency, lowered toxicity, and increased bioavailability. Additional aspects of the invention may include systems and methods for testing FASTmers designed in a high throughput host infection model. In this preferred embodiment, the present inventors may employ a high throughput screening method for the developed FASTmer molecules using: (i) standard broth cultures, and (ii) a host mimicking mammalian infection model that can provide insights about treatment performance in less than 24 hours of experiment. In one preferred embodiment, the invention may include an infection model of pathogenic S. typhimurium strain SL1344-gfp of RAW 264.7 mouse derived macrophages.
Additional aspect of the invention my include one or more of the following preferred embodiment:
1. A method for the rational design and production of therapeutic oligomers comprising:
Additional aims of the inventive technology will be evident from the detailed description and figures presented below.
Aspects, features, and advantages of the present disclosure will be better understood from the following detailed descriptions taken in conjunction with the accompanying figures, all of which are given by way of illustration only, and are not limiting the presently disclosed embodiments, in which:
In one preferred embodiment, the invention include system, methods, and compositions for the rational design of sequence-specific therapies that target specific genes can accelerate development of novel therapeutics. FASTmers, and preferably PNA, offer a promising class of nucleic-acid targeting reagents, which demonstrate strong hybridization and specificity to their targets compared to naturally occurring RNA or DNA. PNAs are synthetic DNA analogs in which the phosphodiester bond is replaced with 2-N-aminoethylglycine units (
As generally shown in
In the preferred embodiment shown in
In this preferred embodiment, a Get Sequences tool may be used for identifying an initial list of PNA candidates and performing preliminary screening of these candidates. The tool may generate a genomic library for a host organism, which may include may take as inputs the following files: a list of gene IDs, a FASTA genome assembly for the target organism, and a corresponding GFF genome annotation file. In addition, it may incorporate the following parameters: PNA sequence length and a pair of gene coordinates relative to the +1 translation start site. The user may also be prompted to select whether they would like sequence warnings and STRING protein analysis to be included in the final output. In this embodiment, the gene IDs provided to the toolbox may represent the genes of the given organism—designated by the genome assembly and annotation files—that the user wishes to target. The Get Sequences tool reads this ID list and, for each list entry, looks through the GFF file for any coding sequence feature (designated in GFF format as “CDS”) or parent gene feature that has a matching identifier. Upon finding a matching coding sequence, the tool extracts the feature name, the start and end genomic coordinates, and the feature strand. A BED file is written with the features corresponding to each ID, and Get Sequences prints output to indicate the matches. The tool then edits the coordinates of this BED file according to the PNA sequence length and the gene coordinates parameters.
The default for PNA length is set to 12, based on competing factors. Prior research has shown a maximum of gene inhibition at PNA lengths of approximately 8 to 12 bases. This is inferred to be related to transport across the cell membrane, which worsens with increased PNA length, and binding strength and specificity, which improves with increased PNA length. However, in our PNA design we wish to minimize the expected number of off-targets in a bacterial genome, which is given by the following equation, under the simplifying assumption of total randomness of the genome (N=PNA length):
In this example, a PNA length of 12 yields sufficient inhibition based on the prior literature and yields less than one expected off-target for even the largest bacterial genomes. Further, gene coordinates parameters may be used to designate a window near the start codon from which to propose PNA sequences. The default window is (−5 , −5) which provides a single PNA sequence that may be complementary to a region starting five bases upstream of the start codon. In one exemplary embodiment, a default 12-mer PNA would be designed to complement the base pattern *****AUG****. This default positioning may be located close to the start codon and have the highest inhibitory effect in prokaryotes. The window may be expanded according to the user's requirements, to produce multiple candidate sequences of the given length. For instance, a window of (−6, −4) with a default 12-mer PNA would produce three PNA candidates, complementary to the following base patterns: ******AUG***, *****AUG****, ****AUG*****, and the like.
In another preferred embodiment, the coordinates and strand designation of each target gene in the original BED file may be used to create a new BED file where each set of genomic coordinates corresponds to the locus that each respective PNA may target. The BEDTools function “getfasta” may then be used to produce a FASTA file of the PNA target sequences from these BED file coordinates and the input genome assembly FASTA file. An output file with the PNA sequences—reverse complements of the target sequences—may also be produced. If the options for sequence warnings and STRING database analysis are selected, these elements may be included in the output file as well. The sequence warnings function analyzes the PNA sequences for possible solubility issues, as well as self-complementary subsequences of more than six bases. The STRING database analysis may provide a network of experimentally verified, computationally predicted, and inferred protein interactions for each target gene, as well as the number of total connections between the genes of this network.
The Find Off-Targets tool may be used to search for incidental alignments between a list of PNA target sequences and a genome assembly. The tool may take as inputs the following files: a FASTA file of PNA target sequences, a FASTA genome assembly, and a corresponding GFF genome annotation file. In addition, it may incorporate the following parameters: the number of allowed alignment mismatches, PNA sequence length, and a pair of gene coordinates relative to the +1 translation start site. The user may also be prompted to select whether the tool should provide as output the total off-target counts for each PNA. The FASTA file of PNA target sequences can either be created manually by the user or taken from the output of the Get Sequences tool. The tool may use Bowtie 2 to align each PNA target sequence in the input FASTA file to the FASTA genome assembly, with the user-specified number of allowed mismatches and using the PNA length parameter as seed length. The default number of allowed mismatches may be set to zero, as many previous studies have demonstrated the high sensitivity of PNA to even a single base mismatch between the PNA and the target nucleic acid. Bowtie 2 produces a SAM alignment file as output, which is processed and indexed using the SAMTools functions “view,” “sort,” and “index.”
The resulting sorted BAM file, produced via SAMTools processing, may be used as input for the BEDTools “window” function. This function is used to identify whether a particular PNA-genome alignment in the BAM file overlaps with any genomic features, as identified by the input GFF genome annotation file. Find Off-Targets may then examine the BED file output of the “window” function to determine which PNA are expected to have off-target alignments in coding sequences, as well as which of these coding sequence alignments occur near to the start codon. These alignments to the start codon region are expected to be inhibitory to gene translation, as discussed previously. The gene coordinate inputs may be used to define the region around the start codon where inhibition is expected. The default for the Find Off-Targets tool is set to (−20, 20), based on prior observations by the inventors which showed minor translation inhibition at 17 bases upstream of a beta-lactamase start codon, but no significant translation inhibition at 23 bases downstream of the same start codon. It should be noted that this parameter is expected to vary from gene to gene, and ordinary experimentation may be required to better estimate whether a given alignment locus may cause translation inhibition.
In this preferred embodiment, the Find Off-Targets tool may produce as output a BED file of all potentially inhibitory PNA alignments. Further, if the off-target counts option was selected, the tool totals the number of potentially inhibitory off-targets for each PNA and provides those sums in a separate file. Off-target predictions may be used as another means of screening PNA candidates, either to avoid targeting other genes within a target genome or to avoid targeting another organism altogether. This function is especially valuable in PNA antibiotic design, as it allows for the design of highly specific antisense PNAs that may avoid broad antibiotic action against a microbiome environment.
As shown in
As generally described above the invention may include the design of one or more customized FASTmers that may regulate expression of a target genes in a host organism. As generally referring to
FASTmers, which may preferably be a PNA or other oligonucleotide sequence such as a dsRNA, or asRNA oligonucleotide may be rapidly produced. In this embodiment, one or more customized FASTmers, which in this embodiment are PNA, may be rapidly generated using solid-phase Fmoc synthesis as generally shown in
In one embodiment, an Apex 396 peptide synthesizer (AAPPTec, LLC) may be used to perform solid-state PNA synthesis using Fmoc chemistry on MBHA rink amide resin at a 10 μmol scale. Fmoc-PNA monomers were obtained from PolyOrg Inc. A, C, and G monomers are protected at amines with Bhoc groups. As shown in
As generally described in
In one preferred embodiment, a PNA may be selected for synthesis according to application-specific needs for sequence stability and specificity, which can be ascertained from the output of the PNA Finder toolbox. In one embodiment, FAST platform synthesis process may include synthesis, purification and drying of the samples. This process may take, in some embodiment four or less days and may further achieve final sample purities of greater than 90%. In one preferred embodiment, testing of the PNA candidate efficacy in MDR bacteria occurs over the course of a 16-hour experiment, where inhibition of each antibiotic PNA is measured against that of a scrambled nonsense sequence. As shown in
In one embodiment, a PNA Finder toolbox may be built using Python 2.7, as well as the alignment program Bowtie 2, the read alignment processing program SAMtools, and the feature analysis program BEDTools. Additionally, in order to run on a Windows operating system, the toolbox may incorporate the program Cygwin to provide a Unix-like environment in which Bowtie 2, SAMtools, and BEDTools can be compiled and run. The user interface for the PNA Finder Toolbox may also constructed using the Python 2.7 package Tkinter, version 8.5.
In a preferred embodiment, clinical isolates may be obtained and grown in Cation Adjusted Mueller Hinton broth (CAMHB) (Becton, Dickinson and Company 212322) at 37° C. with 225 rpm shaking or on solid CAMHB with 1.5% agar at 37° C. Clinical isolates were maintained as freezer stocks in 90% CAMHB, 10% glycerol at −80° C. Freezer stocks were streaked out onto solid CAMHB and incubated for 16 hours to produce single colonies prior to experiments. For each biological replicate, a single colony may be picked from solid media and grown for 16 hours in liquid CAMHB prior to experiments. At the start of experiment, each culture may diluted 1:10,000 in fresh CAMHB and added to either a control experiment without PNA or a 10 uM PNA condition. PNA samples were stored in 5% DMSO to aid in stability.
As used herein, PNAs may be DNA analogs in which the phosphate backbone has been replaced by (2-aminoethyl) glycine carboyl units that are linked to the nucleotide bases by the glycine amino nitrogen and methylene carbonyl linkers. The backbone is thus composed of peptide bonds linking the nucleobases. Because the PNA backbone is composed of peptide linkages, the PNA is typically referred to as having an amino-terminal and a carboxy-terminal end. However, a PNA can be also referred to as having a 5′ and a 3′ end in the conventional sense, with reference to the complementary nucleic acid sequence to which it specifically hybridizes. The sequence of a PNA molecule is described in conventional fashion as having nucleotides G, U, T, A, and C that correspond to the nucleotide sequence of the DNA molecule. Such polynucleotides can be synthesized, for example, using an automated DNA synthesizer. Typically, PNAs are synthesized using either Boc or Fmoc chemistry. PNAs and other polynucleotides can be chemically derivatized by methods known to those skilled in the art. For example, PNAs have amino and carboxy groups at the 5′ and 3′ ends, respectively, that can be further derivatized. Custom PNAs can also be synthesized and purchased commercially. Since PNA is structurally markedly different from DNA, PNA is very resistant to both proteases and nucleases, and is not recognized by the hepatic transporter(s) recognizing DNA.
As used herein, a “FASTmer,” may include an “oligomer” or “therapeutic oligomer” generated using the FAST Platform as generally described herein. In certain embodiments, a FASTmer may include or “antisense oligonucleotides,” which may include any antisense molecule that may modulate the expression of one or more genes. Examples may include antisense PNAs, antisense RNA. This term also encompasses RNA or DNA oligomers such as interfering RNA molecules, such as dsRNA, dsDNA, mRNA, siRNA, or hpRNA as well as locked nucleic acids, BNA, polypeptides and other oligomers and the like.
In yet another embodiment, the PNA comprises at least one modified phosphate backbone selected from the group consisting of a phosphorothioate, a phosphorodithioate, a phosphoramidothioate, a phosphoramidate, a phosphordiamidate, a methylphosphonate, an alkyl phosphotriester, and a formacetal or analog thereof.
As used herein, the term “gene” or “polynucleotide” refers to a single nucleotide or a polymer of nucleic acid residues of any length. The polynucleotide may contain deoxyribonucleotides, ribonucleotides, and/or their analogs and may be double-stranded or single stranded. A polynucleotide can comprise modified nucleic acids (e.g., methylated), nucleic acid analogs or non-naturally occurring nucleic acids and can be interrupted by non-nucleic acid residues. For example, a polynucleotide includes a gene, a gene fragment, cDNA, isolated DNA, mRNA, tRNA, rRNA, isolated RNA of any sequence, recombinant polynucleotides, primers, probes, plasmids, and vectors. Included within the definition are nucleic acid polymers that have been modified, whether naturally or by intervention.
As used herein, the terms “inhibit” and “inhibition” means to reduce a molecule, a reaction, an interaction, a gene, an mRNA, and/or a protein's expression, stability, function, or activity by a measurable amount, or to prevent such entirely. “Inhibitors” are compounds that, e.g., bind to, partially or totally block stimulation, decrease, prevent, delay activation, inactivate, desensitize, or down regulate a protein, a gene, and an mRNA stability, expression, function, and activity, e.g., antagonists.
The term “target sequence,” may mean a nucleotide sequence, such as a DNA sequence, or an mRNA sequence, that may be complementary to antisense molecules, and preferably an antisense peptide nucleic acid.
The term “including” is used herein to mean, and is used interchangeably with, the phrase “including but not limited to.” The term “or” is used herein to mean, and is used interchangeably with, the term “and/or,” unless context clearly indicates otherwise.
The term “therapeutically effective amount” as used herein refers to that amount of a FASTmer composition being administered which will relieve to some extent one or more of the symptoms of the disorder being treated. In reference to the treatment of a bacterial infection, and in particular a MDR infection, a therapeutically effective amount refers to that amount which has the effect of (1) reducing the infection, (2) inhibiting (that is, slowing to some extent, preferably stopping) bacterial growth, (3) inhibiting to some extent (that is, slowing to some extent, preferably stopping) bacterial pathogenicity, and/or (4) relieving to some extent (or, preferably, eliminating) one or more signs or symptoms associated with the infection.
As used herein, “subject” refers to a human or animal subject. In certain preferred embodiments, the subject is a human.
The term “treating”, as used herein, unless otherwise indicated, means reversing, alleviating, inhibiting the progress of, or preventing the disorder or condition to which such term applies, or one or more symptoms of such disorder or condition. The term “treatment”, as used herein, unless otherwise indicated, refers to the act of treating as “treating” is defined immediately above.
It will be recognized by those of skill in the art that any of the DNA or mRNA sequences described above can be targeted by antisense inhibitors. Target sequences can be those of E. Coli or the homologous gene or mRNA sequence in another target bacterium. Given the benefit of this disclosure, those of skill in the art will be able to identify a target sequence and design an antisense inhibitor oligomer to target the gene or mRNA sequence. Target sites on DNA or RNA (e.g. sRNA) associated with antibiotic resistance can be any site to which binding of an antisense oligomer will inhibit the function of the DNA or RNA sequence. Inhibition can be caused by steric interference resulting from an antisense oligomer binding the DNA RNA sequence, thereby preventing proper transcription of the DNA sequence or translation of the RNA sequence.
Certain preferred embodiments provide a FAST pipeline to design and generate PNAs for treating a bacterial infection, and in particular, an MDR bacterial infection. Common drug-resistant bacteria that may include, but not be limited to: carbapenem resistant Enterobacteriaceae Klebsiella pneumonia (CREKP), MDR tuberculosis (MDRTB), MDR Salmonella enterica, MDR Salmonella typhimurium (MDRST), methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant S. aureus (VRSA), extended spectrum β-lactamase Klebsiella pneumoniae (ESBL K. pneumoniae), vancomycin-resistant Enterococcus (VRE), carbapenem-resistant Enterobacteriaceae Escherichia coli (CRE E. Coli), MDR Escherichia coli (MDR E. Coli), New-Delhi metallo-β-lactamase producing Klebsiella pneumoniae (NDM-1 K. pneumoniae) and MDR Acinetobacter baumannii (MRAB).
Examples of suitable probiotic microorganisms that may act as a delivery vehicle for one or more PNAs include yeasts such as Saccharomyces, Debaromyces, Candida, Pichia and Torulopsis, molds such as Aspergillus, Rhizopus, Mucor, and Penicillium and Torulopsis and bacteria such as the genera Bifidobacterium, Bacteroides, Clostridium, Fusobacterium, Melissococcus, Propionibacterium, Streptococcus, Enterococcus, Lactococcus, Staphylococcus, Peptostrepococcus, Bacillus, Pediococcus, Micrococcus, Leuconostoc, Weissella, Aerococcus, Oenococcus and Lactobacillus. Specific examples of suitable probiotic microorganisms are: Saccharomyces cereviseae, Bacillus coagulans, Bacillus licheniformis, Bacillus subtilis, Bifidobacterium bifidum, Bifidobacterium infantis, Bifidobacterium longum, Enterococcus faecium, Enterococcus faecalis, Lactobacillus acidophilus, Lactobacillus alimentarius, Lactobacillus casei subsp. casei, Lactobacillus casei Shirota, Lactobacillus curvatus, Lactobacillus delbruckii subsp. lactis, Lactobacillus farciminus, Lactobacillus gasseri, Lactobacillus helveticus, Lactobacillus johnsonii, Lactobacillus reuteri, Lactobacillus rhamnosus (Lactobacillus GG), Lactobacillus sake, Lactococcus lactis, Micrococcus varians, Pediococcus acidilactici, Pediococcus pentosaceus, Pediococcus acidilactici, Pediococcus halophilus, Streptococcus faecalis, Streptococcus thermophilus, Staphylococcus carnosus, and Staphylococcus xylosus.
As used herein, the term “tool” means a software and/or hardware application that is designed and programed to carry out a specific task or set of tasks.
Naturally as can be appreciated, all of the steps as herein described may be accomplished in some embodiments through any appropriate machine and/or device resulting in the transformation of, for example data, data processing, data transformation, external devices, operations, and the like. It should also be noted that in some instance's software and/or software solution may be utilized to carry out the objectives of the invention and may be defined as software stored on a magnetic or optical disk or other appropriate physical computer readable media including wireless devices and/or smart phones. In alternative embodiments the software and/or data structures can be associated in combination with a computer or processor that operates on the data structure or utilizes the software. Further embodiments may include transmitting and/or loading and/or updating of the software on a computer perhaps remotely over the internet or through any other appropriate transmission machine or device, or even the executing of the software on a computer resulting in the data and/or other physical transformations as herein described.
Certain embodiments of the inventive technology may utilize a machine and/or device which may include a general purpose computer, a computer that can perform an algorithm, computer readable medium, software, computer readable medium continuing specific programming, a computer network, a server and receiver network, transmission elements, wireless devices and/or smart phones, internet transmission and receiving element; cloud-based storage and transmission systems, software updateable elements; computer routines and/or subroutines, computer readable memory, data storage elements, random access memory elements, and/or computer interface displays that may represent the data in a physically perceivable transformation such as visually displaying said processed data. In addition, as can be naturally appreciated, any of the steps as herein described may be accomplished in some embodiments through a variety of hardware applications including a keyboard, mouse, computer graphical interface, voice activation or input, server, receiver and any other appropriate hardware device known by those of ordinary skill in the art.
Any module, unit, component, server, computer, terminal, tool, engine or device exemplified herein that executes instructions may include or otherwise have access to computer readable media such as storage media, computer storage media, or data storage devices (removable and/or non-removable) such as, for example, magnetic disks, optical disks, or tape. Computer storage media may include volatile and non-volatile, removable, and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. Examples of computer storage media include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by an application, module, or both, which specifically includes cloud-based applications. Any such computer storage media may be part of the device or accessible or connectable thereto. Further, unless the context clearly indicates otherwise, any processor or controller set out herein may be implemented as a singular processor or as a plurality of processors. The plurality of processors may be arrayed or distributed, and any processing function referred to herein may be carried out by one or by a plurality of processors, even though a single processor may be exemplified. Any method, application or module herein described may be implemented using computer readable/executable instructions that may be stored or otherwise held by such computer readable media and executed by the one or more processors or through a cloud-based application.
The terminology used herein is for describing embodiments and is not intended to be limiting. As used herein, the singular forms “a,” “and” and “the” include plural referents, unless the content and context clearly dictate otherwise. Thus, for example, a reference to “a target gene” may include a combination of two or more such target genes. Unless defined otherwise, all scientific and technical terms are to be understood as having the same meaning as commonly used in the art to which they pertain.
The invention now being generally described will be more readily understood by reference to the following examples, which are included merely for the purposes of illustration of certain aspects of the embodiments of the present invention. The examples are not intended to limit the invention, as one of skill in the art would recognize from the above teachings and the following examples that other techniques and methods can satisfy the claims and can be employed without departing from the scope of the claimed invention. Indeed, while this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.
Acute radiation syndrome (ARS) or radiation toxicity is an acute illness caused by radiation of part of or whole body by a high dose (>1 Gray or Gy) of radiation for a short period of time. Three classic radiation syndromes include hematopoietic syndrome (HS), also referred to as bone marrow syndrome, gastrointestinal syndrome (GIS), and cardiovascular (CV) or central nervous system (CNS) syndrome. Bone marrow syndrome typically occurs with a dose of 0.7 and 10 Gy. The survival rate of patient's decreases with increasing doses and primary cause of death is destruction of bone marrow which could result in infection and hemorrhage. GI syndrome typically occurs with a dose greater than 10 Gy, and survival is extremely unlikely (typically within 2 weeks) due to irreparable damage to the GI tract. CV or CNS syndrome can occur at doses greater than 50 Gy, though symptoms can occur as low as 20 Gy and considered incurable, with death occurring within 3 days due to collapse of the circulatory system.
The current radiation countermeasures are available for treatment of HS alone or in combination with GIS. HS is driven by loss of crucial growth factor-modulated hematopoietic progenitors and consequently, by large losses of circulating, functional blood cells. This condition has been shown to be treated by Colony-stimulating factors (CSFs), specifically Granulocyte-colony stimulating factor (G-CSF or CSF3) and Granulocyte-macrophage colony-stimulating factor (GM-CSF or CSF2). G-CSF is a glycoprotein produced by monocytes, fibroblasts, and endothelial cells that can induce bone marrow hematopoietic progenitors to differentiate into specific mature blood cell types released into the bloodstream. GM-CSF is a monomeric glycoprotein secreted by macrophages, T-cells, mast cells, natural killer cells, endothelial cells and fibroblasts that functions as a cytokine.
To date, there have been a number of studies involving radiation accidents where ARS patients were treated with G-CSF and GM-CSF cytokines with success. Another key protein playing a role in radiation response includes Erythropoietin (EPO), which is a glycoprotein cytokine which is secreted by the kidney in response to cellular hypoxia and stimulates red blood cell production (erythropoiesis) in the bone marrow. Erythropoietin has been shown to induce cancer cell resistance to ionizing radiation and to cisplatin, and thus can be considered a radiation countermeasure. Another family of proteins, Gamma globulin has been shown to denature after gamma radiation exposure, resulting in formation of insoluble aggregates. Gamma globulin is a protein fraction of blood plasma that responds to stimulation of antigens, such as bacteria or viruses, by forming antibodies. The catabolic rate of gamma globulin has also been shown to increase upon y-ray exposure, with increased rate of gastro-intestinal leakage, as well acute alterations of protein and gene expression.
One embodiment of the invention may include the development of a FAST pipeline to design, built and rapidly test treatments to treat radiation related pathologies. In this embodiment, rationally designed PNAs that can inhibit or activate expression of radiation-responsive genes, such as Granulocyte colony-stimulating factor (G-CSF), 2) granulocyte-macrophage-colony-stimulating factor (GM-CSF), 3) erythropoietin (EPO), and 4) gamma globulin (GG), may allow prevention or reduction of radiation-induced conditions, such as Acute Radiation Syndrome (ARS). In this embodiment, at least two types of PNAs may be generated, specifically, PNA initiators and PNA activators. PNA inhibitors may be single stranded antisense PNAs designed to bind to mRNAs of targeted gene to block translation. PNA activators may be antigene PNAs designed to bind to genomic DNA in the upstream promoter regions of targeted genes to increase gene expression.
In this preferred embodiment, the inventors may rationally design PNAs directed to gene involved in radiation responses within a subject. A PNA finder may be utilized to design a catalog of unique PNA inhibitor and activator molecules against radiation-responsive genes and reduce chances of off-target effects by comparison to gut microbiome and human transcriptome. Once target PNAs have been identified, the inventors may use a semi- or fully-automated PNA synthesis method to generate the target PNAs. In additional embodiments, a Nanoparticle-based delivery strategy may be utilized. Such a nanotechnology delivery system may provide a delivery vehicle for enhanced PNA transport, lowered toxicity, and increased bioavailability. PNAs may be introduced to mammalian cells exposed to radiation, such as gamma (γ)-radiation In this embodiment, the inventors may use a high throughput screening method for the developed PNA molecules using human macrophages, and hematopoietic stem cells exposed to γ-radiation, and in some instances microgravity to better simulate conditions in space. The target PNAs may be tested to demonstrate gene-specificity, reduced radiation response, increased transport, the lowered toxicity.
In one preferred embodiment, the invention may include the design and synthesis of approximately three to five 20-mer PNA molecules that target the translational start site (TIS) or internal ribosome entry site (IRES) of the mRNA encoded by G-CSF, GM-CSF, EPO and GG genes, with the target sequence in the middle of the oligomer, with 3-5 nucleotides flanking the target region (
As shown in
The present inventors developed the first of its kind bioinformatics toolbox for designing PNAs, called PNA finder (
One preferred embodiment of the inventive technology may include the generation of novel PNA molecules configured to be directed against a gene of interest. In one preferred embodiment, PNA molecules may be designed to prevent translation of one or more essential genes within a pathogenic organism, such as MDR strains of Escherichia coli, Salmonella typhimurium, and Klebsiella pneumonia, and Methicillin Resistant Staphylococcus aureus (MRSA). In this embodiment, the present inventors may design a 12-mer PNA molecule that targets the translational start site (TIS) or ribosome binding site (RBS) of the mRNA encoded by an essential gene. Such 12-mer long PNAs may be designed against genes in pathogens using a stepwise targeting method, such that antisense oligomers are designed with the target sequence in the middle of the oligomer, with 3-5 nucleotides flanking the target region.
As shown in
As noted above, in one embodiment, the inventive technology may utilize a software tool generally referred to as PNA finder that may provide sequences of target sites for a given genome using the following algorithm. The criteria for design of species specific PNAs may include: (i) target gene is essential, (ii) evidence that gene silencing of target and/or inhibition of cognate protein is growth inhibitory, (iii) the TIR and RBS sequence is amenable to design of peptide PNAs with low melting temperature, (iv) where possible off-target sites within and between species are not present in TIR and RBS sites, (v) for targeting multiple strains homologues are present in a desired number of species, and (vi) the TIR of the mRNA has at least two base pair between species when designing unique PNAs.
Additionally, the present inventors may perform bioinformatics analysis to identify the start codon sites of essential genes in a range of gram-negative and positive bacteria. The database of essential genes and NCBI BLAST may be used to identify to essential gene homologoues present in the given number of species. In one embodiment, an Artemis program may be used to extract −5 to +5 bases relative to the start codon of the TIR and RBS from the genome sequences relative to start site codon. The 10 bp of TIR and RBS from gene homologues may be aligned using Clustal X version 2.1 and number of mismatches between species may be determined. The predicted thermal stability, as determined by the meting temperature (Tm), of PNA/RNA duplexes may further be determined using mathematical formula reported in Giesen et al. Genomic analysis of possible binding sites may be conducted in Artemis using a cut-off of 2 base pair mismatches.
To examine if the number of predicted PNA sequences can be used to discriminate between closely related species, the present inventors may use a PERL script to identify the start codon positions −5 to +5 relative of each start codon of essential genes. The 10 bp may be used for an all-against-all comparison using a standalone BLAST to design PNAs that are species specific. Off-target binding affinity may be determined at three levels: (i) within the transcriptome of the organism, (ii) across bacterial species, and (ii) human transcriptome. To ensure that the chosen 12-mer does not have sequence homology to any other target inside bacteria, the 12-mer PNA may be aligned using Clustal X version 2.1 to (i) its own bacterial genome, (ii) across desired number of bacterial genomes, (iii) across human transcriptome and genome (for any potential side-effects). Genomic analysis of possible binding sites may also be conducted in Artemis using a cut-off of 2 base pair mismatches. Only PNA sequences that uniquely target bacteria of interested may be considered. For example, in one embodiment, unique PNAs will be designed against known antimicrobial gene sequences obtained from the Comprehensive Antibiotic Resistance Database (CARD).
In one embodiment, the inventive technology may include an automated parallel high-throughput in-lab synthesis capable of producing a plurality of PNAs per run in a short period of time, such as less than a day, based on protocol adopted from Matysiak et al., Weiler et al., and more recently Joshi et al. In this embodiment, PNA oligomers can be synthesized using standard solid phase manual or automated peptide synthesis (such as Prelude peptide synthesizer), using either tert-butyloxycarbonyl (tBoc) or 9-fluorenylmethoxycarbonyl (Fmoc) protected PNA monomers. For example, for PNA-CPP sequence of N terminal-KFFKFFKFFK-AEEA(linker)-CACCGGCAAGTG-C terminal (SEQ ID NO. 1), firstly, the CPP peptide portion (KFF)3K of the PNA-CPP conjugate may be synthesized on the peptide synthesizer using normal automatic mode using a Fmoc-D-Lys (Boc) Wang resin (110 mg, 0.51 mmol/g). This will be followed by PNA synthesis using Fmoc protected PNA monomers with exocyclic amino acid groups of A, T, G and C using the single-shot delivery feature of the machine.
The synthesis of PNA may be started on Fmoc-D-Lys(Boc)-Wang resin (50 mg, 0.78 mmol/g). The Fmoc protecting group can be removed by using 20% piperidine in Dimethyformamide (DMF) twice for 5 min each. This can further be followed by download of resin by partial coupling to free amino acid groups. The unreacted free amino acids may be capped by adding PNA-capping solution (2 ml, for 5 min) containing 5% DIEA. The resin may further be washed and dried. The downloading can be measured in a UV Spectrophotmeter (Nanodrop) at 290 nm. The downloaded resin may be kept in the automated synthesizer, and the coupling (0.5 ml of each PNA monomer, 0.3 ml HATU, and 0.3 ml 196.3 mM DIEA), washing (with DMF, MeOH, and DCM), deprotection, and washing steps may be repeated automatically in a continuous way until and exemplary 12-mer PNA product is obtained—although, as noted elsewhere different sized PNAs may be obtained. The final products of PNA-CPP may be purified with semi-preparative HPLC using C-18 column, and characterized using NMR and MALDI-TOF.
To address the issue of poor PNA transport properties, in one embodiment, the inventive technology may repurpose bacterial secretion systems, such as Type III (T3SS) or Type IV secretion systems, to deliver PNAs. Notably, T3SS are molecular machines used by many gram-negative bacterial pathogens including pathogens Shigella, Yersinia, Salmonella and Pseudomonas, to inject proteins, known as effectors, directly into eukaryotic host cells. These proteins manipulate host signal transduction pathways and cellular processes to the pathogen's advantage.
As generally shown in
In another preferred embodiment shown in
In one embodiment, PNAs generated by the FAST system pipeline may undergo in vitro screening in broth cultures. Bacterial cultures of each individual gram negative and gram positive strain may be grown in broth or other appropriate medium. PNA molecules may be designed for each strain to either target them individually or in combinatorial manner. Scrambled PNA sequence may be used as control. PNAs would be supplied in a range of concentrations (0-50 μM) to the various combination of cultures for a period of 24 hours. The number of viable cells remaining at the end of this time point may be measured using colony forming unit analysis. The dominant strains in the culture would be identified by sampling liquid culture at end of experiment and measuring relative distribution of the strains using pathogen specific primers in a quantitative PCR assay.
As generally shown in
In this embodiment, the present inventors may infect at time zero with a multiplicity of infection (MOI) of 90 bacteria for each host cell, and 70% of macrophages become infected. Forty-five minutes after infection an antibiotic, such as gentamicin may be added [100 μg/mL final] to kill remaining extracellular bacteria. At 2 hours post-infection, the medium may be replaced with fresh medium containing PNAs over a dose range (0-50 μM) or DMSO (control) and gentamicin [10 μg/mL] to prevent replication of any remaining extracellular bacteria. At 18 hours post infection, cells are incubated with MitoTracker® (red, an indicator of mitochondrial membrane potential), fixed with 2.5% paraformaldehyde, and incubated with DAPI (blue). Two 10× images from each well in 3 different channels (red, blue, green) are captured on an automated microscope, the Cellomics ArrayScan VTI HCS Reader (Thermo Scientific) in the HTS facility. Quantitative image analysis may be automated using MATLAB. In this embodiment a target parameter may include the average area of GFP+ pixels, normalized to total area within the macrophage. This methodology is quantitative, unbiased, and can process samples faster than is possible manually. All images may be cataloged and stored for future reference and reanalysis as needed. 504, of supernatant may use to determine lactate dehydrogenase release as a measure of cytotoxicity using the Pierce LDH cytotoxicity assay kit.
The present inventor utilized the Facile Accelerated Specific Therapeutic (FAST) platform to create gene-specific antisense peptide nucleic acids (PNAs) molecules designed to inhibit protein translation. FAST PNAs were designed to inhibit the pathways identified in our transcriptomic analysis, and each PNA was then tested in combination with each carbapenem to assess its effect on the antibiotics' minimum inhibitory concentrations. We observed significant treatment interaction with five different PNAs across six PNA-antibiotic combinations. Inhibition of the genes hycA, dsrB, and bolA were found to re-sensitize CRE E. Coli to carbapenems, whereas inhibition of the genes flhC and ygaC was found to confer added resistance.
To validate the E. Coli CUS2B resistance phenotype observed in the clinic, we measured the isolate's minimum inhibitory concentrations (MIC) for a variety of antibiotics from different classes (
The present inventors performed whole genome shotgun sequencing for two purposes: (1) to create a genome assembly that could be used for antisense PNA design, and (2) to search for genomic contributions to the resistance phenotype. Using the ARG-ANNOT database, we found that the strain encodes fifteen genes related to antibiotic resistance (
The present inventors have established the ability of PNA and the FAST platform to design effective antibiotic potentiators through the use of genomic data, using either knockouts of essential genes or resistance genes. Here, FAST PNA allow us to explore transcriptomic analysis and determine whether it can be similarly useful in reversing a bacterial resistance_phenotype. First, to reveal possible non-genetic contributions to the strain's carbapenem_resistance profile, we exposed exponentially growing E. Coli CUS2B to ertapenem and_meropenem and examined gene expression profiles after thirty and sixty minutes of treatment (
The present inventors identified differentially expressed (DE) genes by comparing the RNA sequencing data from ertapenem- and meropenem-treated samples to an untreated control at the same timepoint. The DESeq R package was used to evaluate significance and correct P-values for multiple hypothesis testing. General expression trends were evaluated using hierarchical clustering across genes and conditions (
The gene ivy, an inhibitor of bactericidal vertebrate lysozymes, was overexpressed in both treatments at 30 and 60 minutes. Both lysozymes and carbapenems disrupt peptidoglycan polymerization, although ivy is not known to interact with these antibiotics. Three other transcripts of unknown function were overexpressed in all conditions: BTW13_RS03610 (ymgD superfamily), BTW13_RS11940 (DUF1176 superfamily), and a transcript antisense to BTW13_RS17895 (putative lipoprotein, DUF1615 superfamily). In the ertapenem response we find many more DE genes than in the meropenem response, including 38 DE genes shared between the two time points (compared with none shared across both meropenem time points). Within this set, we observed significant overrepresentation of genes related to maltodextrin transport (mal operon, GO:0042956) and the ferredoxin hydrogenase complex (hyc operon, GO:0009375). All of these overrepresented genes were found to be overexpressed in ertapenem treatments. Only three genes were underexpressed in ertapenem at both 30 and 60 minutes: 1ptG, a member of the lipopolysaccharide transport system, phoH, an ATP-binding protein, and cstA, a starvation induced peptide transporter. Of the genes specific to the meropenem response, only the flagellar biosynthesis proteins fliQ and fliT are related, and the downregulation of these genes did not continue to the 60-minute timepoint.
The present inventors also searched for differential expression in outer membrane porin operon (omp) genes, previously linked to carbapenem-resistance, and resistance-related genes identified by ARG-ANNOT. Of the omp operon, only ompF was found to be significantly DE in any condition with respect to no treatment (underexpressed in meropenem, 30 minutes), while ompA and ompC expression tracked closely with the no treatment conditions in all experiments. When expression levels of the ertapenem and meropenem experiments were directly compared at each time point, none of the three genes were found to be significantly DE. No resistance-related genes were DE in any condition.
Based on these observations, we chose three genes to target using PNA: hycA, malT, and flhC. The former two genes were chosen to probe the hyc and mal operons for their importance to resistance and their utility as antibiotic re-sensitization targets. The gene flhC was chosen to validate the consistent downregulation of the FlhDC system and evaluate whether further knockout of the gene would confer greater carbapenem resistance.
In addition to total RNA sequencing, we performed small RNA sequencing to search for resistance contributions and potential FAST PNA targets among short nucleic acids potentially involved in gene regulation. Small RNA have been previously shown to influence bacterial stress and antibiotic response. We used an RNA isolation protocol that enriched for sRNA (see_Methods) prior to sequencing, and sequencing data were aligned to the E. Coli UMN026 genome_ (the reference that maximized alignment homology) using the Rockhopper pipeline, which allowed for identification of previously documented sRNA and novel RNAs._We observe more overlap of DE genes between single time points than between_respective antibiotic treatments, suggesting a generalized and transient response similar to that_of total RNA expression (
The FAST platform comprises Design, Build, and Test modules for the creation of antisense PNA (
Based on the results of our transcriptomic analysis, we selected three 235 genes identified by our total RNA sequencing analysis (hycA, malT, and flhC) and three genes identified by our small RNA sequencing analysis (bolA, dsrB, and ygaC) to be targeted by FAST PNA. Differential expression of flhC and bolA was observed in both carbapenems, while differential expression of hycA, dsrB, and the operon controlled by malT was prevalent in the ertapenem response. The transcript antisense to ygaC was overexpressed in both meropenem conditions, but the gene itself was not differentially expressed. While we suspect that the ygaC antisense transcript regulates the gene ygaC, PNA have not been established to interfere with ncRNA regulation. With this in mind, we designed a PNA to bind to the ygaC sense transcript and inhibit protein translation, to test the hypothesis that ygaC inhibition may confer greater meropenem resistance in a similar manner to the flhC-targeted PNA. The genome assembly for the clinical isolate was used by FAST to design multiple PNA for each selected gene, which were then screened for high solubility, minimal self-complementarity, and zero off-target gene inhibition in E. Coli CUS2B. Additionally, a scrambled-sequence nonsense PNA was designed to control for any possible effects of the PNA or CPP independent of sequence. No effects were found with nonsense PNA alone or in any nonsense PNA-antibiotic combination treatment. We also designed a PNA to inhibit the translation of the chromosomal β-lactamase AmpC, based on prior research showing that the enzyme can elevate ertapenem MICs. This PNA was also synthesized to assess the relative effectiveness of PNA targets selected using transcriptomic analysis, in comparison to those selected on a genomic basis.
We have previously shown the ability to re-sensitize MDR bacteria by targeting β-lactamases. In a combination of α-ampC (10 μM) in combination with ertapenem (1 μg/mL), we also observe significant synergistic interaction, evidenced both by the growth curve endpoint and cell viability assay (Table 1). E. Coli CUS2B cultures treated with a combination of 0.1 μg/mL meropenem with 10 μM α-ampC grew similarly to cultures treated with meropenem alone, as expected. Although the comparison of treatments in the cell viability assay did demonstrate significant interaction, the data does not seem to indicate a combinatorial effect, as the fluorescence level is virtually unchanged across the three treated conditions. Additionally, increasing the concentration of α-ampC to 15 μM could not resolve any effect, as the PNA alone was virtually lethal at this concentration. To determine whether transcriptomic analysis could be used by FAST to produce similar re-sensitization effects, E. Coli CUS2B was treated with each of the six PNA at a concentration of 10 μM in combination with sub-MIC carbapenem treatments (1 μg/mL ertapenem, 0.1 μg/mL meropenem). We analyzed the cultures' endpoint optical densities and cell viabilities (via resazurin assay) to assess interaction between the two treatments, based on a comparison with each individual PNA and carbapenem treatment. At these concentrations of PNA and antibiotic, we observed significant synergy between the PNAs α-hycA, α-dsrB, and α-bolA and ertapenem, with S-values of 0.23, 0.85 and 0.83 for their respective endpoint optical densities (Table 1,
The PNA α-ygaC, α-malT, and α-flhC at concentrations of 10 μM did not exhibit significant interaction with ertapenem at 1 μg/mL or meropenem at 0.1 μg/mL. As noted above, we hypothesized that a combination of the PNA α-flhC or α-ygaC with carbapenem treatment would result in a recovery of growth and increased resistance. However, in the PNA-carbapenem combination treatments we did not observe growth recovery relative to the carbapenem-only treatment for the sub-MIC concentrations. We hypothesized that effects at such concentrations could be difficult to resolve, given that the growth curves of carbapenem treated E. Coli CUS2B reached endpoints similar to the untreated condition.
To examine this hypothesis, we treated the clinical isolate with α-flhC or α-ygaC at 10 μM in combination with ertapenem or meropenem at their MICs (
E. Coli CUS2B was provided the Dr. Nancy Madinger, at the University of Colorado Hospital Clinical Microbiology Laboratory's organism bank. The isolate was obtained via rectal swab from a 29-year old pregnant female patient. Unless otherwise mentioned, CUS2B was propagated in aerobic conditions at 37° C. in liquid cultures of cation-adjusted Mueller Hinton broth (CAMHB) with shaking at 225 rpm or on solid CAMHB with 15 g/L of agar. Minimum inhibitory concentration assays Three colonies were picked from a plate and used to inoculate three separate overnight cultures in 1 mL CAMHB each. After 16 hours, the cultures were diluted 1:10,000 and treated with a range of antibiotic concentrations, decreasing in 2-fold increments, in a 384 or 96-well microplate using three biological replicates per condition. Growth in the plate was monitored with a Tecan GENios (Tecan Group Ltd.) running Magellan™ software (v 7.2) at an absorbance of 461 590 nm every 20 minutes for 16 hours, with shaking between measurements. The minimum inhibitory concentration was identified as the lowest antibiotic concentration preventing growth.
Five colonies were picked from a plate and resuspended in liquid culture. After 16 hours, 1 mL of culture was used for genomic DNA isolation with the Wizard DNA Purification Kit (Promega). Approximately 2 μg of DNA was used to prepare a paired-end 250-bp sequencing library with the Nextera XT DNA library kit. The library was sequenced on an Illumina MiSeq, resulting in 407,910 reads (20× coverage). The de novo assembly is 5,325,941 bp in length with a GC content of 50.59%. The largest contig is 394,969 bp, and the N50 is 100,215. The genome contains 5,360 protein coding sequences, 114 RNA coding sequences, 82 tRNAs, 11 ncRNAs, 260 pseudogenes, and 2 CRISPR arrays. The FASTQ files were filtered for quality using Trimmomatic (v0.32), in sliding window 473 mode with a window size of 4 bases, a minimum average window quality of 15 (phred 33 quality aligned to various E. Coli RefSeq reference genomes using Bowtie 2 (v2.2.3). SAMTools (v0.1.19) was used to remove PCR duplicates and create indexed, sorted BAM files. Variants were called and filtered using the Genome Analysis Toolkit (v2.4-9). To pass the filter, a SNP had to meet the following criteria: QD<2.0, FS >60, MQ<40.0, ReadPosRankSum <−2.0, and MappingQualityRankSum <−12.5. Filter criteria for indels was: QD <2.0, FS >60.0, and ReadPosRankSum <−2.0. A custom Python script was used to annotate variant call files using the corresponding GFF from RefSeq. For de novo assembly, reads were assembled using SPAdes (v 3.5.0) and annotation was performed with the NCBI Prokaryotic Genome Annotation Pipeline (v 4.0). Quality of the assembly was assessed using QUAST90. The FASTA generated by SPAdes was used for MLST, identification of resistance genes with ARG-ANNOT, locating CRISRRs with CRISPRfinder, and locating plasmids with PlasmidFinder.
Colonies were picked from a plate and resuspended in liquid culture. After 16 hours of growth, the culture was diluted 1:20 into duplicate 15 mL cultures. These were grown for 1 hour, then 3 mL from each was preserved in 2 volumes of RNAprotect. Each culture was divided into three equal parts. No antibiotic was added to one part and antibiotic were added to the other two for final concentrations of 2 μg/mL of ertapenem or 1 μg/mL of meropenem, corresponding to 50% of the MIC under these growth conditions (note that these conditions are different than the procedures used to determine the MICs in
PNA design was carried out using the PNA Finder toolbox. The toolbox is built using Python 2.7, the alignment program Bowtie 2, the read alignment processing program SAMtools, and the feature analysis program BEDTools. The toolbox takes a user-provided list of gene IDs and cross-references the IDs against a genome annotation file to determine the feature coordinates for each ID. The toolbox then uses these coordinates to extract PNA target sequences of a user-specified length (12 bases in this study) and user-specified positions relative to the start codon from a genome assembly FASTA file. PNA Finder provides a list of PNA candidates (the reverse complements of the target sequences) and sequence warnings regarding solubility and self-complementation. Finally, PNA Finder screens the list of PNA candidates against a user-provided genome assembly (in this study, the genome for E. Coli CUS2B) to search for off-targets and uses this analysis to filter the candidates into a final PNA list for synthesis.
PNA were synthesized using an Apex 396 peptide synthesizer (AAPPTec, LLC) with solid-phase Fmoc chemistry at a 10 μmol scale on MBHA rink amide resin. Fmoc-PNA monomers were obtained from PolyOrg Inc., with A, C, and G monomers protected with Bhoc groups. PNA were synthesized with the N-terminal cell-penetrating peptide (KFF) K. Cell-penetrating peptide Fmoc monomers were obtained from AAPPTec, LLC, and lysine monomers were protected with Boc groups. PNA products were precipitated in diethyl ether and purified as trifluoroacetic acid salts via reverse-phase HPLC using a C18 column.
Three colonies were picked from a plate and used to inoculate three separate overnight cultures in 1 mL CAMHB each. After 16 hours, the culture was diluted 1:10,000 in a 384-well microplate using three biological replicates per condition. The total culture volume for each treatment was 50 μL. PNA were stored at −20° C. dissolved in 5% v/v DMSO in water. Growth in the plate was monitored with a Tecan GENios (Tecan Group Ltd.) running Magellan™ software (v 7.2) at an absorbance of 590 nm every 20 minutes for 24 hours, with shaking between measurements. Interaction effects were evaluated for significance using a two-way ANOVA test, and S values were calculated with respect for the expected growth inhibition as calculated by the Bliss Independence model. The S-value for a given timepoint was calculated as follows:
For a given timepoint (24 hours was used in our analyses), the variable ODAB represents optical density with only carbapenem treatment, OD0 represents the optical density without treatment, ODPNA represents optical density with only antisense-PNA treatment, and ODAB, PNA represents the optical density with a combination treatment. Plus/minus for S-values (Table 1) was calculated by propagating standard error values for each term in Equation 1. Other software and resources utilized The clustergram function from MATLAB's Bioinformatics toolbox was used for building heatmaps and dendograms. A Euclidean distance metric, optimal leaf ordering, and average linkage function were used for clustering. Ecocyc was used to gain gene names and descriptions and to define functional classes. NCBI's BLAST was used to predict gene function and to determine similarity of sequences in CUS2B to other bacterial strains. PANTHER was used for statistical overrepresentation tests, with a Bonferroni correction applied to all reported P574 values.
The whole genome shotgun sequencing data has been deposited at DDBRENA/GenBank under the accession MSDR00000000.1. The version described in this invention is version MSDR01000000. The RNA sequencing data has been deposited in NCBI's Sequence Read Archive under the accession SRP101716.
This International PCT Application claims the benefit of and priority to U.S. Provisional Application No. 62/884,974, filed Aug. 9, 2020. The entire specification, claims, and figures of the above-referenced application are hereby incorporated, in their entirety by reference.
This invention was made with government support under grant number D17AP00024 awarded by DOD/DARPA, and Grant number NNX16A069A awarded by NASA. The government has certain rights in the invention.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US20/45638 | 8/10/2020 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 62884974 | Aug 2019 | US |
