Antibiotic-mediated microbial community restructuring is dictated by variability in antibiotic susceptibility and population interactions.

It is widely known that faster-growing bacterial cells are more susceptible to antibiotics. Given this notion, it appears intuitive that antibiotic treatment would enrich slower-growing cells in a clonal population or slower-growing populations in a microbial community, which has been commonly observed. However, experimental observations also show the enrichment of faster-growing subpopulations under certain conditions. Does this apparent discrepancy suggest uniqueness about different growth environments or the role of additional confounding factors? If so, what could be the major determinant in antibiotic-mediated community restructuring? Combining modeling and quantitative measurements using a barcoded heterogeneous E. coli library, we show that the outcome of antibiotic-mediated community restructuring can be driven by two major factors. One is the variability among the clonal responses of different subpopulations to the antibiotic; the other is their interactions. Our results suggest the importance of quantitative measurements of antibiotic responses in individual clones in predicting community responses to antibiotics and addressing subpopulation interactions.

Data-driven learning of structure augments quantitative prediction of biological responses.

Multi-factor screenings are commonly used in diverse applications in medicine and bioengineering, including optimizing combination drug treatments and microbiome engineering. Despite the advances in high-throughput technologies, large-scale experiments typically remain prohibitively expensive. Here we introduce a machine learning platform, structure-augmented regression (SAR), that exploits the intrinsic structure of each biological system to learn a high-accuracy model with minimal data requirement. Under different environmental perturbations, each biological system exhibits a unique, structured phenotypic response. This structure can be learned based on limited data and once learned, can constrain subsequent quantitative predictions. We demonstrate that SAR requires significantly fewer data comparing to other existing machine-learning methods to achieve a high prediction accuracy, first on simulated data, then on experimental data of various systems and input dimensions. We then show how a learned structure can guide effective design of new experiments. Our approach has implications for predictive control of biological systems and an integration of machine learning prediction and experimental design.

A generic approach to infer community-level fitness of microbial genes.

The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.

Promotion of plasmid maintenance by heterogeneous partitioning of microbial communities.

Transferable plasmids play a critical role in shaping the functions of microbial communities. Previous studies suggested multiple mechanisms underlying plasmid persistence and abundance. Here, we focus on the interplay between heterogeneous community partitioning and plasmid fates. Natural microbiomes often experience partitioning that creates heterogeneous local communities with reduced population sizes and biodiversity. Little is known about how population partitioning affects the plasmid fate through the modulation of community structure. By modeling and experiments, we show that heterogeneous community partitioning can paradoxically promote the persistence of a plasmid that would otherwise not persist in a global community. Among the local communities created by partitioning, a minority will primarily consist of members able to transfer the plasmid fast enough to support its maintenance by serving as a local plasmid haven. Our results provide insights into plasmid maintenance and suggest a generalizable approach to modulate plasmid persistence for engineering and medical applications.

Differences in Palliative Care Provision by Primary and Specialist Providers Supporting Patients With COVID-19: A Qualitative Study.

Objectives: To describe the delivery of palliative care by primary providers (PP) and specialist providers (SP) to hospitalized patients with COVID-19. Methods: PP and SP completed interviews about their experiences providing palliative care. Results were analyzed using thematic analysis. Results: Twenty-one physicians (11 SP, 10 PP) were interviewed. Six thematic categories emerged. Care provision: PP and SP described their support of care discussions, symptom management, managing end of life, and care withdrawal. Patients provided care: PP described patients at end of life, with comfort-focused goals; SP included patients seeking life-prolonging treatments. Approach to symptom management: SP described comfort, and PP discomfort in providing opioids with survival-focused goals. Goals of care: SP felt these conversations were code status-focused. Supporting family: both groups indicated difficulties engaging families due to visitor restrictions; SP also outlined challenges in managing family grief and need to advocate for family at the bedside. Care coordination: internist PP and SP described difficulties supporting those leaving the hospital. Conclusion: PP and SP may have a different approach to care, which may affect consistency and quality of care.

Physician perceptions of restrictive visitor policies during the COVID-19 pandemic: a qualitative study.

BACKGROUND: Little is understood of the consequences of restrictive visitor policies that were implemented in hospitals to minimize risk of infection during the COVID-19 pandemic. The objective of this study was to describe physician experiences with these policies and reflections of their effects. METHODS: We conducted semistructured phone interviews from September 2020 to March 2021 with physicians practising in Ontario hospitals, recruited via professional networks and snowball sampling. We audio-recorded, transcribed and analyzed interviews to describe and interpret overarching themes by thematic analysis. RESULTS: We interviewed 21 physicians (5 intensivists, 5 internists, 11 specialists in palliative care). Four main thematic categories emerged, including provider, system, patient and caregiver effects. Provider-related factors included increased time and effort on communication with a need to establish limits; increased effort to develop rapport with caregivers; lack of caregiver input on patient care; the need to act as a caregiver surrogate; and the emotional toll of being a gatekeeper or advocate for visitors, exacerbated by lack of evidence for restrictions and inconsistent enforcement. System effects included the avoidance of hospital admission and decreased length of stay, leading to readmissions, increased deaths at home and avoidance of transfer to other facilities with similar policies. Patient-related factors included isolation and dying alone; lack of caregiver advocacy; and prioritization of visitor presence that, at times, resulted in a delay or withdrawal of aspects of care. Caregiver-related factors included inability to personally assess patient health, leading to poor understanding of patient status and challenging decision-making; perceived inadequate communication; difficulty accessing caregiver supports; and increased risk of complicated grief. Participants highlighted a disproportionate effect on older adults and people who did not speak English. INTERPRETATION: Our study highlights substantial negative consequences of restrictive visitor policies, with heightened effects on older adults and people who did not speak English. Research is required to identify whether the benefits of visitor restrictions on infection control outweigh the numerous deleterious consequences to patients, families and care providers.

Horizontal gene transfer enables programmable gene stability in synthetic microbiota.

The functions of many microbial communities exhibit remarkable stability despite fluctuations in the compositions of these communities. To date, a mechanistic understanding of this function-composition decoupling is lacking. Statistical mechanisms have been commonly hypothesized to explain such decoupling. Here, we proposed that dynamic mechanisms, mediated by horizontal gene transfer (HGT), also enable the independence of functions from the compositions of microbial communities. We combined theoretical analysis with numerical simulations to illustrate that HGT rates can determine the stability of gene abundance in microbial communities. We further validated these predictions using engineered microbial consortia of different complexities transferring one or more than a dozen clinically isolated plasmids, as well as through the reanalysis of data from the literature. Our results demonstrate a generalizable strategy to program the gene stability of microbial communities.

Identifying barriers and facilitators to palliative care integration in the management of hospitalized patients with COVID-19: A qualitative study.

BACKGROUND: Palliative care is well suited to support patients hospitalized with COVID-19, but integration into care has been variable and generally poor. AIM: To understand barriers and facilitators of palliative care integration for hospitalized patients with COVID-19. METHODS: Internists, Intensivists and palliative care physicians completed semi-structured interviews about their experiences providing care to patients with COVID-19. Results were analysed using thematic analysis. RESULTS: Twenty-three physicians (13 specialist palliative care, five intensivists, five general internists) were interviewed; mean ± SD age was 42 ± 11 years and 61% were female. Six thematic categories were described including: patient and family factors, palliative care knowledge, primary provider factors, COVID-19 specific factors, palliative care service factors, and leadership and culture factors. Patient and family factors included patient prognosis, characteristics that implied prognosis (i.e., age, etc.), and goals of care. Palliative care knowledge included confidence in primary palliative care skills, misperception that COVID-19 is not a 'palliative diagnosis', and the need to choose quantity or quality of life in COVID-19 management. Primary provider factors included available time, attitude, and reimbursement. COVID-19 specific factors were COVID-19 as an impetus to act, uncertain illness trajectory, treatments and outcomes, and infection control measures. Palliative care service factors were accessibility, adaptability, and previous successful relationships. Leadership and culture factors included government-mandated support, presence at COVID planning tables, and institutional and unit culture. CONCLUSION: The study findings highlight the need for leadership support for formal integrated models of palliative care for patients with COVID-19, a palliative care role in pandemic planning, and educational initiatives with primary palliative care providers.

Intra- and interpopulation transposition of mobile genetic elements driven by antibiotic selection.

The spread of genes encoding antibiotic resistance is often mediated by horizontal gene transfer (HGT). Many of these genes are associated with transposons, a type of mobile genetic element that can translocate between the chromosome and plasmids. It is widely accepted that the translocation of antibiotic resistance genes onto plasmids potentiates their spread by HGT. However, it is unclear how this process is modulated by environmental factors, especially antibiotic treatment. To address this issue, we asked whether antibiotic exposure would select for the transposition of resistance genes from chromosomes onto plasmids and, if so, whether antibiotic concentration could tune the distribution of resistance genes between chromosomes and plasmids. We addressed these questions by analysing the transposition dynamics of synthetic and natural transposons that encode resistance to different antibiotics. We found that stronger antibiotic selection leads to a higher fraction of cells carrying the resistance on plasmids because the increased copy number of resistance genes on multicopy plasmids leads to higher expression of those genes and thus higher cell survival when facing antibiotic selection. Once they have transposed to plasmids, antibiotic resistance genes are primed for rapid spread by HGT. Our results provide quantitative evidence for a mechanism by which antibiotic selection accelerates the spread of antibiotic resistance in microbial communities.

Modulation of microbial community dynamics by spatial partitioning.

Microbial communities inhabit spatial architectures that divide a global environment into isolated or semi-isolated local environments, which leads to the partitioning of a microbial community into a collection of local communities. Despite its ubiquity and great interest in related processes, how and to what extent spatial partitioning affects the structures and dynamics of microbial communities are poorly understood. Using modeling and quantitative experiments with simple and complex microbial communities, we demonstrate that spatial partitioning modulates the community dynamics by altering the local interaction types and global interaction strength. Partitioning promotes the persistence of populations with negative interactions but suppresses those with positive interactions. For a community consisting of populations with both positive and negative interactions, an intermediate level of partitioning maximizes the overall diversity of the community. Our results reveal a general mechanism underlying the maintenance of microbial diversity and have implications for natural and engineered communities.

Pulmonary referrals to specialist palliative medicine: a survey.

OBJECTIVES: Patients with chronic respiratory disease have significant palliative care needs, but low utilisation of specialist palliative care (SPC) services. Decreased access to SPC results in unmet palliative care needs among this patient population. We sought to determine the referral practices to SPC among respirologists in Canada. METHODS: Respirologists across Canada were invited to participate in a survey about their referral practices to SPC. Associations between referral practices and demographic, professional and attitudinal factors were analysed using regression analyses. RESULTS: The response rate was 64.7% (438/677). Fifty-nine per cent of respondents believed that their patients have negative perceptions of palliative care and 39% were more likely to refer to SPC earlier if it was renamed supportive care. While only 2.7% never referred to SPC, referral was late in 52.6% of referring physicians. Lower frequency of referral was associated with equating palliative care to end-of-life care (p<0.001), male sex of respirologist (p=0.019), not knowing referral criteria of SPC services (p=0.015) and agreement that SPC services prioritise patients with cancer (p=0.025); higher referral frequency was associated with satisfaction with SPC services (p=0.001). Late referral was associated with equating palliative care to end-of-life care (p<0.001) and agreement that SPC services prioritise patients with cancer (p=0.013). CONCLUSIONS: Possible barriers to respirologists' timely SPC referral include misperceptions about palliative care, lack of awareness of referral criteria and the belief that SPC services prioritise patients with cancer. Future studies should confirm these barriers and evaluate the effectiveness of strategies to overcome them.

Design patterns for engineering genetic stability.

The past 20 years have witnessed enormous progress in synthetic biology in the development of engineered cells for diverse applications, including biomanufacturing, materials fabrication, and potential therapeutics and diagnostics. However, it still remains a major challenge to maintain long-term performance of synthetic gene circuits, due to the emergence of mutants that lose circuit function. Here, we highlight major vulnerabilities of synthetic gene circuits resulting in circuit failure and mutant escape. We also discuss engineering strategies to enhance long-term circuit stability and performance. These approaches can be divided into two strategies: the suppression of the emergence of mutants and the suppression of their relative fitness if mutants do emerge. We anticipate that mechanistic understanding of the modes of circuit failure will facilitate future efforts to design evolutionarily robust synthetic biology-inspired applications.

Predicting plasmid persistence in microbial communities by coarse-grained modeling.

Plasmids are a major type of mobile genetic elements (MGEs) that mediate horizontal gene transfer. The stable maintenance of plasmids plays a critical role in the functions and survival for microbial populations. However, predicting and controlling plasmid persistence and abundance in complex microbial communities remain challenging. Computationally, this challenge arises from the combinatorial explosion associated with the conventional modeling framework. Recently, a plasmid-centric framework (PCF) has been developed to overcome this computational bottleneck. This framework enables the derivation of a simple metric, the persistence potential, to predict plasmid persistence and abundance. Here, we discuss how PCF can be extended to account for plasmid interactions. We also discuss how such model-guided predictions of plasmid fates can benefit from the development of new experimental tools and data-driven computational methods.

The Role of Coffee and its Bioactive Components in Platelet Function and Aging.

Cardiovascular diseases (CVD) are known to be the world's leading cause of death and different factors are known to increase the risk of death, including aging, mainly due to increased oxidative stress and inflammation observed in older people. Acute myocardial infarctions and cerebrovascular accidents belong to CVD, and are the ones that cause the most deaths and disabilities, where greater platelet activation plays an important role in pathophysiology. These diseases are more prevalent in older people, which have a clear relationship with increased platelet function and are strongly related to aging. Platelet function is affected by diet, which varies in its requirements and characteristics according to age. Coffee belongs to the family of diet elements that can alter platelet function and an increase in coffee consumption with advancing age, and a U-shaped correlation with the risk of CVD have been reported. However, the effect of coffee consumption and its bioactive compounds on platelet function and aging presents controversial evidence, and therefore, a complex effect is not fully elucidated in the cardiovascular system. This review focuses on the relationship between coffee consumption (and its constituent bioactive compounds), and platelet function, and aging.

Effectiveness of a Multiprofessional, Online and Simulation-Based Difficult Conversations Training Program on Self-Perceived Competence of Oncology Healthcare Provider Trainees.

Effective communication between healthcare providers (HCPs) and patients is important for HCP well-being, patient engagement, and health outcomes. Yet, HCPs do not receive adequate communication skills training and report feeling unprepared for difficult conversations. A needs assessment of 64 cancer HCP trainees in Toronto, Canada, found that a majority of trainees rated themselves with low competency in communication skills to support patients through difficult conversations, while nearly all rated these skills as important to their practice. A blended multiprofessional communications program was developed including online theoretical learning and reflective practice in addition to in-person simulation with standardised patient actors. Since communication skills mastery is highly unlikely to occur at the termination of a single training program, the goal of the program was to stimulate participants' motivational beliefs about difficult conversations communication skills in order to deepen their commitment to learning and mastery. The motivational beliefs assessed included self-efficacy (self-perceived competence), intent to use techniques learned, and confidence in task mastery. After completing the course, participants' self-perceived competence in dealing with difficult conversations significantly increased by an average of 25 points (p < 0.001) on a rating scale of 1-100 (n = 40). Participants' intent to use techniques did not change significantly and remained high with an overall average of 89 points. After the course, participants rated their confidence in mastering techniques learned at an average score of 71 points. Multiprofessional, simulation-based training is an effective way to improve HCP trainees' motivational beliefs around having difficult conversations.

Optimized Combination of HDACI and TKI Efficiently Inhibits Metabolic Activity in Renal Cell Carcinoma and Overcomes Sunitinib Resistance.

Clear cell renal cell carcinoma (ccRCC) is characterized by high histone deacetylase (HDAC) activity triggering both cell motility and the development of metastasis. Therefore, there is an unmet need to establish innovative strategies to advance the use of HDAC inhibitors (HDACIs). We selected a set of tyrosine kinase inhibitors (TKIs) and HDACIs to test them in combination, using the validated therapeutically guided multidrug optimization (TGMO) technique based on experimental testing and in silico data modeling. We determined a synergistic low-dose three-drug combination decreasing the cell metabolic activity in metastatic ccRCC cells, Caki-1, by over 80%. This drug combination induced apoptosis and showed anti-angiogenic activity, both in original Caki-1 and in sunitinib-resistant Caki-1 cells. Through phosphoproteomic analysis, we revealed additional targets to improve the translation of this combination in 3-D (co-)culture systems. Cell-cell and cell-environment interactions increased, reverting the invasive and metastatic phenotype of Caki-1 cells. Our data suggest that our optimized low-dose drug combination is highly effective in complex in vitro settings and promotes the activity of HDACIs.

Optimized low-dose combinatorial drug treatment boosts selectivity and efficacy of colorectal carcinoma treatment.

The current standard of care for colorectal cancer (CRC) is a combination of chemotherapeutics, often supplemented with targeted biological drugs. An urgent need exists for improved drug efficacy and minimized side effects, especially at late-stage disease. We employed the phenotypically driven therapeutically guided multidrug optimization (TGMO) technology to identify optimized drug combinations (ODCs) in CRC. We identified low-dose synergistic and selective ODCs for a panel of six human CRC cell lines also active in heterotypic 3D co-culture models. Transcriptome sequencing and phosphoproteome analyses showed that the mechanisms of action of these ODCs converged toward MAP kinase signaling and cell cycle inhibition. Two cell-specific ODCs were translated to in vivo mouse models. The ODCs reduced tumor growth by ~80%, outperforming standard chemotherapy (FOLFOX). No toxicity was observed for the ODCs, while significant side effects were induced in the group treated with FOLFOX therapy. Identified ODCs demonstrated significantly enhanced bioavailability of the individual components. Finally, ODCs were also active in primary cells from CRC patient tumor tissues. Taken together, we show that the TGMO technology efficiently identifies selective and potent low-dose drug combinations, optimized regardless of tumor mutation status, outperforming conventional chemotherapy.

Integrating Phenotypic Search and Phosphoproteomic Profiling of Active Kinases for Optimization of Drug Mixtures for RCC Treatment.

Combined application of multiple therapeutic agents presents the possibility of enhanced efficacy and reduced development of resistance. Definition of the most appropriate combination for any given disease phenotype is challenged by the vast number of theoretically possible combinations of drugs and doses, making extensive empirical testing a virtually impossible task. We have used the streamlined-feedback system control (s-FSC) technique, a phenotypic approach, which converges to optimized drug combinations (ODC) within a few experimental steps. Phosphoproteomics analysis coupled to kinase activity analysis using the novel INKA (integrative inferred kinase activity) pipeline was performed to evaluate ODC mechanisms in a panel of renal cell carcinoma (RCC) cell lines. We identified different ODC with up to 95% effectivity for each RCC cell line, with low doses (ED5-25) of individual drugs. Global phosphoproteomics analysis demonstrated inhibition of relevant kinases, and targeting remaining active kinases with additional compounds improved efficacy. In addition, we identified a common RCC ODC, based on kinase activity data, to be effective in all RCC cell lines under study. Combining s-FSC with a phosphoproteomic profiling approach provides valuable insight in targetable kinase activity and allows for the identification of superior drug combinations for the treatment of RCC.

Identification of low-dose multidrug combinations for sunitinib-naive and pre-treated renal cell carcinoma.

BACKGROUND: Combinations of drugs can improve the efficacy of cancer treatment, enable the reduction of side effects and the occurrence of acquired drug resistance. METHODS: We approached this challenge mathematically by using the validated technology called the Therapeutically Guided Multidrug Optimization (TGMO) method. In a set of genetically distinct human renal cell carcinoma (RCC) cell lines, either treated chronically with sunitinib (-ST) or sunitinib-naive, we identified cell line-specific low-dose-optimised drug combinations (ODC). RESULTS: Six cell-type-specific low-dose drug combinations for three sunitinib-naive as well as three sunitinib pre-treated cells were established. These ODCs effectively inhibited the RCC cell metabolic activity while being ineffective in non-cancerous cells. Based on a single screening test and three searches, starting with ten drugs, we identified highly efficacious drug mixtures containing four drugs. All ODCs contained AZD4547 (FGFR signalling pathway inhibitor) and pictilisib (pan-phosphatidylinositol 3-kinase inhibitor), but varied in the third and fourth drug. ODC treatment significantly decreased cell metabolic activity (up to 70%) and induced apoptosis, independent of the pretreatment with sunitinib. The ODCs outperformed sunitinib, the standard care for RCC. Moreover, short-term starvation potentiated the ODC activity. The translation of the 2D-based results to 3D heterotypic co-culture models revealed significant inhibition of the spheroid growth (up to 95%). CONCLUSION: We demonstrate a promising low-dose drug combination development to obtain drug combinations effective in naive as well as resistant tumours. Nevertheless, we emphasise the need for further mechanistic investigation and preclinical development.

Effect of lyophilization on the physicochemical and rheological properties of food grade liposomes that encapsulate rutin.

The potential use of liposomes as carriers for food active ingredients can be limited by their physical and chemical instabilities in aqueous dispersions, especially for long-term storage. Lyophilization, a process commonly used in the food industry, can also be applied to stabilize and preserve liposomes and to extend their shelf-life. In this work, liposomes with potential use for designing functional foods were prepared with soy phospholipids and rutin. Homogenization and ultrasound were used for particle size reduction. Liposomal stability was evaluated by Dynamic Light Scattering, microscopy and rheological properties. Spherical and unilamellar liposomes were obtained in this work. Zeta potential (ξ = values were around -40 mV), which indicates a great suspension stability even for more than 30 days of storage. Rutin exerted a protective effect by both preventing damage to the liposome bilayer and maintaining the spherical structure after 56 days of storage. Lyophilization caused an increase in the size of the vesicles, reaching sizes around 419 nm and aggregation of vesicles with probably structural damage after 21 storage days. However, it helped to keep the rutin encapsulated (81.9%) for longer time, when compared to refrigerated liposomes. Rheological measurements showed, in general, that the power law model fitted most of the experimental results and dynamic rheological tests showed a sol-gel phase transition between 35 and 45 °C. Lyophilization caused a significant change in all evaluated rheological parameters. For the in vitro release tests, the liposomal bilayer acted as a barrier for the rutin release to the food simulating medium; therefore, the release rate of the antioxidant from the rutin encapsulated liposome was slow compared to the free rutin release rate.