Host range is a major determinant in the industrial utility of a bacteriophage. A model host range permits broad recognition across serovars of a target bacterium while avoiding cross-reactivity with commensal microbiota. Searching for a naturally occurring bacteriophage with ideal host ranges is challenging, time-consuming, and restrictive. To address this, SPTD1.NL, a previously published luciferase reporter bacteriophage for Salmonella, was used to investigate manipulation of host range through receptor-binding protein engineering. Similar to related members of the Ackermannviridae bacteriophage family, SPTD1.NL possessed a receptor-binding protein gene cluster encoding four tailspike proteins, TSP1-4. Investigation of the native gene cluster through chimeric proteins identified TSP3 as the tailspike protein responsible for Salmonella detection. Further analysis of chimeric phages revealed that TSP2 contributed off-target Citrobacter recognition, whereas TSP1 and TSP4 were not essential for activity against any known host. To improve the host range of SPTD1.NL, TSP1 and TSP2 were sequentially replaced with chimeric receptor-binding proteins targeting Salmonella. This engineered construct, called RBP-SPTD1-3, was a superior diagnostic reporter, sensitively detecting additional Salmonella serovars while also demonstrating improved specificity. For industrial applications, bacteriophages of the Ackermannviridae family are thus uniquely versatile and may be engineered with multiple chimeric receptor-binding proteins to achieve a custom-tailored host range.

Engineered luciferase reporter bacteriophages provide specific, sensitive, rapid and low-cost detection of target bacteria and address growing diagnostic needs in multiple industries. Detection of methicillin-resistant Staphylococcus aureus (MRSA) nasal colonization and antibiotic susceptibility play a critical supportive role in preventing hospital-acquired infections and facilitating antibiotic stewardship. We describe the development and evaluation of a novel phage-based MRSA diagnostic screen for nasal swab specimens. The screen utilizes two luciferase reporter phages capable of recognizing genetically-diverse Staphylococcus aureus. The beta-lactam antibiotic cefoxitin is included to differentiate between resistant (MRSA) and susceptible organisms. The screen positively identified 97.7% of 390 clinical MRSA isolates at low bacterial concentrations. At higher inoculums, 93.5% of 123 clinical non-MRSA Staphylococcus aureus yielded appropriate negative results. Although cross-reactivity of the phage cocktail was observed with other staphylococcal and bacillus species, these false positives were absent under selective conditions. MRSA remained detectable in the presence of 38 distinct competing species and was accurately identified in 100% of 40 spiked nasal specimens. Thus, this six-hour screen sensitively detected MRSA both in vitro and in human nasal matrix.

Bacteriophages have been investigated for clinical utility, both as diagnostic tools and as therapeutic interventions. In order to be applied successfully, a detailed understanding of the influence of the human matrix on the interaction between bacteriophage and the host bacterium is required. In this study, a cocktail of luciferase bacteriophage reporters was assessed for functionality in a matrix containing human serum and spiked with Staphylococcus aureus. The inhibition of signal and loss of sensitivity was evident with minimal amounts of serum. This phenotype was independent of bacterial growth and bacteriophage viability. Serum-mediated loss of signal was common, albeit not universal, among S. aureus strains. Immunoglobulin G was identified as an inhibitory component and partial inhibition was observed with both the f(ab’)₂ and Fc region. A modified bacteriophage cocktail containing recombinant protein A was developed, which substantially improved signal without the need for additional sample purification. This study highlights the importance of assessing bacteriophage activity in relevant host matrices. Furthermore, it identifies an effective solution, recombinant protein A, for promoting bacteriophage-based detection of S. aureus in matrices containing human serum.

Background: KEYNOTE-522 resulted in FDA approval of the immune checkpoint inhibitor pembrolizumab in combination with neoadjuvant chemotherapy for patients with early-stage, high-risk, triple-negative breast cancer (TNBC). Unfortunately, pembrolizumab is associated with several immune-related adverse events (irAEs). We aimed to identify potential tumor microenvironment (TME) biomarkers which could predict patients who may attain pathological complete response (pCR) with chemotherapy alone and be spared the use of anti-PD-1 immunotherapy. Methods: Comprehensive immune profiling, including RNA-seq gene expression assessment of 395 immune genes, was performed on matched FFPE tumor samples from 22 stage I-III TNBC patients (14 patients treated with neoadjuvant chemotherapy alone (NAC) and 8 treated with neoadjuvant chemotherapy combined with pembrolizumab (NAC+I)). Results: Differential gene expression analysis revealed that in the NAC group, IL12B and IL13 were both significantly associated with pCR. In the NAC+I group, LCK and TP63 were significantly associated with pCR. Patients in both treatment groups exhibiting pCR tended to have greater tumor inflammation than non-pCR patients. In the NAC+I group, patients with pCR tended to have greater cell proliferation and higher PD-L1 expression, while in the NAC group, patients with pCR tended to have lower cancer testis antigen expression. Additionally, the NAC+I group trended toward a lower relative dose intensity averaged across all chemotherapy drugs, suggesting that more dose reductions or treatment delays occurred in the NAC+I group than the NAC group. Conclusions: A comprehensive understanding of immunologic factors could potentially predict pCR to chemotherapy alone, enabling the avoidance of the unnecessary treatment of these patients with checkpoint inhibitors.

Disparities in cancer diagnosis, treatment, and outcomes based on self-identified race and ethnicity (SIRE) are well documented, yet these variables have historically been excluded from clinical research. Without SIRE, genetic ancestry can be inferred using single-nucleotide polymorphisms (SNPs) detected from tumor DNA using comprehensive genomic profiling (CGP). However, factors inherent to CGP of tumor DNA increase the difficulty of identifying ancestry-informative SNPs, and current workflows for inferring genetic ancestry from CGP need improvements in key areas of the ancestry inference process. This study used genomic data from 4274 diverse reference subjects and CGP data from 491 patients with solid tumors and SIRE to develop and validate a workflow to obtain accurate genetically inferred ancestry (GIA) from CGP sequencing results. We use consensus-based classification to derive confident ancestral inferences from an expanded reference dataset covering eight world populations (African, Admixed American, Central Asian/Siberian, European, East Asian, Middle Eastern, Oceania, South Asian). Our GIA calls were highly concordant with SIRE (95%) and aligned well with reference populations of inferred ancestries. Further, our workflow could expand on SIRE by (i) detecting the ancestry of patients that usually lack appropriate racial categories, (ii) determining what patients have mixed ancestry, and (iii) resolving ancestries of patients in heterogeneous racial categories and who had missing SIRE. Accurate GIA provides needed information to enable ancestry-aware biomarker research, ensure the inclusion of underrepresented groups in clinical research, and increase the diverse representation of patient populations eligible for precision medicine therapies and trials.