Altered nuclease activity has been associated with different human conditions, underlying its potential as a biomarker. The modular and easy to implement screening methodology presented in this paper allows the selection of specific nucleic acid probes for harnessing nuclease activity as a biomarker of disease.
Nucleases are a class of enzymes that break down nucleic acids by catalyzing the hydrolysis of the phosphodiester bonds that link the ribose sugars. Nucleases display a variety of vital physiological roles in prokaryotic and eukaryotic organisms, ranging from maintaining genome stability to providing protection against pathogens. Altered nuclease activity has been associated with several pathological conditions including bacterial infections and cancer. To this end, nuclease activity has shown great potential to be exploited as a specific biomarker. However, a robust and reproducible screening method based on this activity remains highly desirable.
Herein, we introduce a method that enables screening for nuclease activity using nucleic acid probes as substrates, with the scope of differentiating between pathological and healthy conditions. This method offers the possibility of designing new probe libraries, with increasing specificity, in an iterative manner. Thus, multiple rounds of screening are necessary to refine the probes' design with enhanced features, taking advantage of the availability of chemically modified nucleic acids. The considerable potential of the proposed technology lies in its flexibility, high reproducibility, and versatility for the screening of nuclease activity associated with disease conditions. It is expected that this technology will allow the development of promising diagnostic tools with a great potential in the clinic.
Nucleases are a class of enzymes capable of cleaving the phosphodiester bonds that form the backbone structure of nucleic acid molecules. The vast diversity of nucleases makes their classification rather difficult. However, there are some common criteria used to describe nucleases, such as substrate preference (deoxyribonucleic acid (DNA) or ribonucleic acid (RNA)), cleavage site (endonucleases or exonucleases), or metal ion dependency, among others1. Nucleases are highly conserved catalytic enzymes that have fundamental roles in both, prokaryotic and eukaryotic organisms and have been used, and continue to be used, as gene editing tools2. They are also fundamental actors in DNA maintenance and replication, helping to keep genome stability and participating in proof-reading processes3. In bacteria, for example, nucleases have been identified as important virulence factors, able to promote bacterial survival by reducing the efficacy of the host's immune system4,5,6,7,8. In mammals, nucleases have been suggested to be implicated in apoptosis9, mitochondrial biogenesis and maintenance10 and mediation of antibacterial and antiviral innate immune responses11. Not surprisingly, nuclease activity alterations, whether enhancement or lack of, have been implicated in a wide array of human diseases. These diseases range from a wide variety of cancers12,13 to cardiac hypertrophy10 or autoimmune diseases14. Therefore, nucleases have become interesting candidates as biomarkers for a heterogeneous group of human conditions. In fact, nucleases have already shown their potential as successful diagnostic tools for the detection of infections caused by specific bacterial agents, such as Staphylococcus aureus or Escherichia coli15,16. In many cancer types, expression of staphylococcal nuclease domain-containing protein 1 (SND1) ribonuclease is indicative of poor prognosis17. In pancreatic cancer patients, elevated ribonuclease I (RNase I) serum levels have been reported18 and proposed to be associated with cancerous cell phenotypes19. In ischemic heart conditions, such as myocardial infarction or unstable angina pectoris, deoxyribonuclease I (DNase I) serum levels have been shown to be a valid diagnostic marker20,21.
It has been hypothesized that the global blueprint of nuclease activity may be different in healthy and disease states. In fact, recent reports have used differences in nuclease activity to distinguish between healthy and cancerous phenotypes22 or to identify pathogenic bacterial infections in a species-specific manner15,23. These findings have opened a new avenue for the use of nucleases as biomarkers of disease. Therefore, there exists a necessity for the development of a comprehensive screening method able to systematically identify disease associated differences in nuclease activity, which may be of key importance in the development of new diagnostic tools.
Herein, we introduce and describe a new in vitro screening approach (Figure 1) to identify sensitive and specific probes capable of discriminating between nuclease activity in healthy and unhealthy, or activity specific to a type of cell or bacteria. Taking advantage of the modularity of nucleic acids, we designed an initial library of quenched fluorescent oligonucleotide probes consisting of a comprehensive set of different sequences and chemistries, both being important parameters for library design. These oligonucleotide probes are flanked by a fluorophore (fluorescein amidite, FAM) and a quencher (tide quencher 2, TQ2) at the 5' and 3' ends respectively (Table 1). By using this fluorescent resonance energy transfer (FRET) based fluorometric assay to measure the kinetics of enzymatic degradation, we were able to identify candidate probes with the potential to discriminate differential patterns of nuclease activity associated with healthy or disease states. We designed an iterative process, in which new libraries are created based on the best candidate probes, that allows the identification of ever more specific candidate probes in subsequent screening steps. Moreover, this approach takes advantage of the catalytic nature of nucleases to increase sensitivity. This is achieved by taking advantage of the activatable nature of the reporter probes and the ability of nucleases to continually process substrate molecules, both representing key advantages over alternative antibody or small molecule-based screening methods.
This approach offers a highly modular, flexible and easy to implement screening tool for the identification of specific nucleic acid probes capable of discriminating between healthy and disease states, and an excellent platform for the development of new diagnostic tools that can be adapted for future clinical applications. As such, this approach was used to identify the nuclease activity derived from Salmonella Typhimurium (herein referred to as Salmonella) for the specific identification of this bacteria. In the following protocol, we report on a method to screen for bacterial nuclease activity using kinetic analysis.
1. Oligonucleotide library design and preparation
2. Bacterial culture
3. Supernatant preparation
4. Nuclease Activity Assay
5. Screening Rounds’ Selection Criteria (Figure 1)
Figure 1 shows the work flow of this methodology, which is divided into two screening rounds. In the first round of screening, we used 5 DNA probes (DNA, DNA Poly A, DNA Poly T, DNA Poly C and DNA Poly G) and also 5 RNA probes (RNA, RNA Poly A, RNA Poly U RNA Poly C and RNA Poly G). The raw data of this screening round can be found in Supplementary Table 1. In the second round, chemically modified probes were synthesized by replacing the RNA sequence with chemically modified nucleosides (All 2'-Fluoro and All 2'-OMethyl) or by the combination of RNA and purines or pyrimidines chemically modified (RNA Pyr-2'F, RNA Pyr-2'OMe, RNA Pur-2'F and RNA Pur-2'OMe). The raw data of this screening round can be found in Supplementary Table 2. A detailed description of the sequences can be found in Table 1. The results obtained from the first screening round are shown in Figure 2, where Salmonella culture supernatants report a clear preference for RNA probes over DNA probes. In contrast, E. coli and culture media controls show very limited capability to degrade RNA probes. In addition, we have calculated the fold difference (FD) between the rate coefficients of Salmonella and E.coli (Supplementary Table 3 and Supplementary Table 4) in order to identify the best performing probes. The calculations were performed as described in the protocol section.
These results suggest the presence of an RNase type of activity derived from Salmonella. Based on the identification of RNA as the preferred nucleic acid type for Salmonella nucleases, we have designed a new library using chemically modified nucleotides to be used in the second round of screening aimed at increasing the specificity of the probes. Figure 3 shows the kinetic profiles of the probes containing chemically modified nucleotides. Interestingly, RNA Pyr-2'OMe and RNA Pur-2'OMe show the best performing kinetic behavior when compared with RNA Pyr-2'F and RNA Pur-2'F, respectively.
These results suggest that Salmonella has an important RNase activity that can be used for selecting probes capable of specifically recognizing this bacteria. Moreover, we observed that 2'-OMe chemically modified nucleosides are more suitable for the type of RNAses secreted by Salmonella. With this in mind, the protocol described in this contribution offers the possibility of exploring the use of nuclease activity as a biomarker.
Figure 1: Bacteria cultures and workflow of the screening process. Preparation of bacteria cultures and supernatants (left). Description of the workflow for the two screening rounds. First screening: The preference for DNA or RNA is evaluated using 10 probes. Second screening: Based on nucleic acid preference, additional probes containing chemically modified nucleotides are evaluated to identify the best performing substrates for a given nuclease activity. Please click here to view a larger version of this figure.
Figure 2: First kinetic screening round. Kinetic profiles of Salmonella, E. coli and culture media (TSB) using DNA and RNA probes. Nuclease activity is represented by relative fluorescence units (RFU). The graphs are representative for at least 3 individually performed experiments. The different samples are labeled as indicated in the graph's legend. Fold difference (FD) values were calculated using the rate coefficients of Salmonella and E. coli for each probe. Please click here to view a larger version of this figure.
Figure 3: Second kinetic screening round. Kinetic profiles of Salmonella, E. coli and culture media (TSB) using chemically modified probes. Nuclease activity is represented by relative fluorescence units (RFU). The graphs are representative for at least 3 individually performed experiments. The different samples are labeled as indicated in the graph's legend. Fold difference (FD) values were calculated using the rate coefficients of Salmonella and E.coli for each probe. Please click here to view a larger version of this figure.
Table 1: Nucleic acid probe sequences. List of all the nucleic acid probes used in this study. Please click here to view a larger version of this figure.
Supplementary Figure 1: Measurement set up. Button clicks and dialog windows describing the stepwise process performed in the acquisition software to set up the different measurement parameters. (A) Desktop icon. (B) Task manager dialog window. (C) Procedure and Temperature Set up dialog windows. (D) Procedure and Kinetic Step dialog windows. (E) Procedure and Read Method dialog windows. Please click here to view a larger version of this figure.
Supplementary Figure 2: Measurement set up. Button clicks and dialog windows describing the stepwise process performed in the acquisition software to set up the different measurement parameters. (A) Procedure and Read Step (Kinetic) Dialog windows. (B) Procedure dialog window (C) "Protocol" menu bar. (D) Well selection dialog window. (E) File name input box. (F) Run New icon used to start the acquisition within the software. Please click here to view a larger version of this figure.
Supplementary Figure 3: Data analysis. Button clicks and dialog windows describing the stepwise process performed in the acquisition software to export acquired data into a spread sheet for further analysis. (A) Plate Matrix dialog window. (B) Plate and Well Selection dialog windows. (C) Plate dialog window and Quick Export context menu. Please click here to view a larger version of this figure.
Supplementary Figure 4: Third screening round (Sequence preference optimization). Description of the different steps involved in an additional screening round aimed at assessing sequence variations. Please click here to view a larger version of this figure.
Supplementary Figure 5: Fourth screening round (Specificity evaluation round). Description of the different steps involved in an additional screening round aimed at increasing specificity. Please click here to view a larger version of this figure.
Supplementary Figure 6: Fifth screening round (Reaction parameter optimization). Description of the different steps involved in an additional screening round aimed at reducing non-target cross reactivity by modulating nuclease activity. Please click here to view a larger version of this figure.
Supplementary Table 1: Raw data from the first screening round. For each probe (labeled in red, on top), the acquisition time and the raw fluorescence values were reported for TSB, E. coli and Salmonella, along with the calculated rate value for each interval. The calculations were carried out as described in the methods section. Please click here to download this file.
Supplementary Table 2: Raw data from the second screening round. For each probe (labeled in red, on top), the acquisition time and the raw fluorescence values were reported for TSB, E. coli and Salmonella, along with the calculated rate value for each interval. The calculations were carried out as described in the methods section. Please click here to download this file.
Supplementary Table 3: Data analysis for the first screening round. For each probe (labeled in red, on top), the following values were obtained for TSB, E. coli and Salmonella: maximum rate values, minimal and maximal interval time points, rate coefficient, fold difference values between Salmonella and E. coli over TSB and fold difference values between Salmonella and E. coli (highlighted in yellow). The calculations were carried out as described in the methods section and the calculation formulas and the step by step calculations are shown in the spreadsheet. Please click here to download this file.
Supplementary Table 4: Data analysis for the second screening round. For each probe (labeled in red, on top), the following values were obtained for TSB, E. coli and Salmonella: maximum rate values, minimal and maximal interval time points, rate coefficient, fold difference values between Salmonella and E. coli over TSB and fold difference values between Salmonella and E. coli (highlighted in yellow). The calculations were carried out as described in the methods section and the calculation formulas and the step by step calculations are shown in the spreadsheet. Please click here to download this file.
Alterations of nuclease activity have been associated with a wide variety of disease phenotypes, including different types of cancer and bacterial infections. These alterations are proposed to be the causative agent of a condition14, while in other cases they are the consequence of a detrimental physiological event20 or pathogenic agent16,26. Not surprisingly, attempts to use nucleases and nuclease activity as a diagnostic biomarker have been described15,22,23,26, with considerable promise. Accordingly, the establishment of a robust and reproducible screening approach for the systematic evaluation of nuclease activity in disease and for the identification of specific and sensitive reporter seems pertinent. To address this necessity, we have developed a robust, modular and easy to implement screening platform based on a fluorescence assay, that allows the discovery of novel disease biomarkers and the identification of sensitive and specific nucleic acid probes in parallel, by using the catalytic action of nucleases.
Powerful screening tools such as small molecule high throughput screening (HTS)27, systematic evolution of ligands by exponential enrichment (SELEX)28 or phage display29 have been previously reported, which allow the identification of high affinity recognition molecules (e.g., small molecules, aptamers or binding-peptides). In comparison, the screening approach presented here allows the selection of probes that can identify known and unknown nuclease activity. Furthermore, this approach is compatible with in vitro, ex vivo and in vivo screening models. Moreover, the reactive nature of nucleases confers an obvious advantage over the aforementioned approaches, in that the probe-nuclease interaction is not a static, but a dynamic process. This means that the nucleases' activity becomes an intrinsic signal amplification module for the reporter probes since several reporter probes can interact with a single nuclease.
As in any other screening method, the generation and management of the initial library is essential. The nature of nucleic acid probes provides great flexibility in the design and creation of a library and allows the introduction of varying degrees of complexity depending on the screening application. Library complexity can be introduced at different levels including sequence motifs, nucleotide chemistry, phosphate backbone chemistry, and oligonucleotide length. Modulating the complexity of the library allows to identify probes, not only for their capacity to successfully identify nuclease activity associated with disease but also for properties compatible with subsequent in vivo applications. Furthermore, a nucleic acid base library offers several advantages over its antibody or peptide counterparts. On the one hand, antibody production is well known to be cumbersome, requiring animals or complex eukaryotic culture systems, which increase the cost and introduce batch variability30,31. Moreover, the high molecular weight and immunogenicity limit their application28,32. On the other hand, the generation of biological peptide libraries usually requires either viral or bacterial expression systems29,30, increasing the complexity of the screening process. Chemical peptide libraries avoid this problem, at the expense of using convoluted bead-based systems or multiple rounds of expensive peptide synthesis33. All these problems are circumvented by using a nucleic acid library. Once the initial library has been established, the screening methods are quick and straightforward. The method described herein serves as a platform for additional screening rounds, such as, sequence optimization (Supplementary Figure 4), specificity evaluation (Supplementary Figure 5) or optimization of modulatory elements of nuclease activity, such as metal cofactors (typically divalent cations) and chelators, which are very useful to increase the specificity of the selected probes (Supplementary Figure 6).
The kinetic fluorometric assay used in this study can be optimized for both, bacterial and cellular cultures, with the screening being performed in user-friendly microtiter plates. In the case of cellular assays, this protocol is compatible with both, suspension and monolayer cultures, which, post-optimization, can be used according to the necessities of the in vitro model being studied. We have identified several critical steps that require optimization prior to screening. These include the cell number or bacterial density to be assayed, probe concentration, fluorometer detector gain settings or the implementation of in-built background correction methods. One limitation of this technology is the need for an altered nuclease activity associated with the pathological condition of interest. Without this feature, the screening approach for the selection of candidate probes is not feasible. Another limitation is the self-quenching ability of guanines when they are in close proximity to the fluorophore. This characteristic needs to be considered when designing the library.
The enzymatic nature of the reaction being measured makes it necessary to consider plate loading times. Minimizing loading times will reduce background differences between different experimental conditions. Several options exist to overcome this problem, such as slowing the enzymatic reaction during loading by using ice-cold reagents, or using automated loading systems, though the latter increases costs considerably, but also the throughput. Moreover, kinetic measurements are a great improvement over static measurements, providing a complete and more realistic picture of the dynamics of nucleases' catalytic activity.
In summary, our protocol offers a versatile, robust and reproducible screening method for the identification of sensitive and specific nucleic acid probes for the detection of nuclease activity associated with the disease, which overcomes major hurdles of alternative screening methods. We anticipate that this screening technology will allow the development of novel diagnostic tools in a multitude of conditions, with easy translatability to the clinic.
The authors have nothing to disclose.
The authors would like to acknowledge Luiza I. Hernandez (Linköping University) for her careful revision of the manuscript and valuable advice. This work was supported by The Knut and Alice Wallenberg Foundation and The Swedish Government Strategic Research Area in Materials Science on Advanced Functional Materials at Linköping University (Faculty Grant SFO-Mat-LiU No. 2009-00971).
Black bottom, non-treated 96 well plate | Fisher Scientific | 10000631 | |
Cytation1 | BioTek | CYT1FAV | |
Eppendorf tubes | Thermofisher | 11926955 | |
Escherichia coli | ATCC | 25922 | |
Microbank cryogenic storage vial containing beads | Pro-Lab Diagnostics | 22-286-155 | |
Nucleic acid probes | Biomers.net | # | |
Phosphate Buffer Saline containing MgCl2 and CaCl2 | Gibco™ | 14040117 | |
Salmonella enterica subs. Enterica | ATCC | 14028 | |
Tris-EDTA | Fisher Scientific | 10647633 | |
Tryptone Soya Agar with defibrinated sheep blood | Thermo Fisher Scientific | 10362223 | |
Tryptic Soy Broth | Sigma Aldrich | 22092 |