Co-designed all experiments and co-analyzed all experimental results; developed the theoretical tools and performed all calculations; co-developed image analysis channel in ImageJ; developed computer tools for the startup process; co-developed a microscopic assay to study the luminal content of gavad mice particles used in Figure 5.1C and 1D;. Contributed, designed and analyzed data from experiments involving oral administration of particles in Figure 5.1; performed, designed and analyzed data from all ex vivo aggregation experiments in SI fluid in Figures S2 and 5.S5; performed, designed and analyzed data from all GPC measurements in Figures and Tables 5.S1-7; performed, designed and analyzed data from all in vitro aggregation experiments with PEG solutions in Figure 5.4D, Figure 5.4—figure supplements 1-2 and with dietary fiber in Figure 5.7A;. Designed and co-designed the project; initially observed the clustering phenomenon described in this work; co-designed and co-analyzed preliminary experiments; performed preliminary ex vivo and in vitro aggregation experiments; co-developed a microscopic assay to study the luminal content of gavad mice particles used in Figure 5.1C and 5.1D;.
Co-developed the image analysis pipeline in ImageJ; co-analyzed the ex vivo collection data in Figure 5.2; co-designed and co-analyzed preliminary ex vivo collection experiments with MUC2KO mice; provided useful advice on designing the bootstrapping procedure; co-interpreted results; co-wrote the paper. Preliminary experiments conducted together; developed fluorescence laser scanning approaches for examining the luminal contents of mice engrafted with particles shown in Figure 5.1A and 5.1B; Particles administered to mice in Figure 5.1; co-developed approach to extract the liquid fraction of mouse intestinal contents; co-transfer and MUC2KO colony initialization; genotyping setup of MUC2KO mice; helped supervise the husbandry of the MUC2KO colony; helped with the interpretation of the results; co-wrote the paper.
LIST OF ILLUSTRATIONS AND TABLES
176 Table 5.S1: Estimates of polymer physical parameters from gel permeation chromatography for liquid fractions from the upper small intestine of MUC2 knockout (MUC2KO) and wild-type (WT) mice. 177 Table 5.S2: Estimates of polymer physical parameters from gel permeation chromatography for liquid fractions from the lower small intestine of MUC2 knockout (MUC2KO) and wild-type (WT) mice. 179 Table 5.S4: Estimates of polymer physical parameters from gel permeation chromatography for liquid fractions from the lower small intestine of immunoglobulin-deficient (Rag1KO) and wild-type WT mice.
180 Table 5.S6: Estimates of physical parameters of polymers from gel permeation chromatography for liquid fractions of upper small intestine from pectin and Fibersol-2 fed mice. 181 Table 5.S7: Estimates of physical parameters of polymers from gel permeation chromatography for liquid fractions of lower small intestine from pectin and Fibersol-2-fed mice.
AN OVERVIEW
In my research, I have found great utility in "digital" microfluidics: a process in which individual molecules can be placed in a small compartment, a reaction run, and the total number of molecules counted by the presence or absence of the reaction product in each compartment . In addition, we are studying the impact that a patient's DNA (which is likely to be present in urine samples and clinical swabs) can have on the detection of the sexually transmitted bacterial infection chlamydia. These beads could be loaded onto murine intestinal mucosa, and the thickness of the mucosa could be quantified in response to the introduction of different sized polymers, some naturally occurring in the diet.
These beads are very useful for many additional applications; at the time of publication of this thesis, the beads were used in two additional studies that are not further described in the thesis. I developed a method that uses chromatography (a technique for separating molecules based on their tendency to partition into oil and water-like materials) along with their mass to simultaneously quantify how many of these 35 different bile acids exist in a given section of the gastrointestinal tract. tract.
REAL-TIME, DIGITAL LAMP WITH COMMERCIAL MICROFLUIDIC CHIPS REVEALS THE INTERPLAY OF EFFICIENCY, SPEED, AND
TEMPERATURE AND TIME
I Summary of MATLAB script functions In order to quantify the reactions on chips using the Poisson distribution, we needed to know
The advantage of using only the detectable partitions that reached the minimum fluorescence intensity (out of a total of 20,000 partitions per chip) was a reduced total computational time because only a fraction of all partitions were tracked in real time. The temperature of the thermocycler block was maintained at 25 °C to initiate all reactions, with the exception of the experiment where the block was preheated to the optimal temperature (Figure 2.S2b). The quantification of the C:T ratio remained consistent (and the sensitivity call the same) because we use a ratiometric calculation.
The tail factor was calculated as the total width of the tip at 5% lift (or the distance from the leading edge to the time of tip lift (“f0.05”) plus the distance from the time of tip lift to the tail end ( "b0.05")) divided by twice the distance from the leading edge to the tip rise time. Bar graphs of the location of the peak time of the distribution curve (time in the positive mode) using Bst 2.0 (a) and Bst 3.0 (b).
VI Hardware and pre-heating considerations We asked if multiple instrumentation formats could be used to collect the data and if
Effect of hardware and heating on (a) the distribution in time to fluorescence threshold and (b) quantification of amplification efficiency (mean percentage of copies observed ± S.D.) at 40. Following the protocol previously described18, buffer conditions for Bst were 2.0 optimized in bulk at 713 copies/µL (eg ~4,280 or 0 copies per 6 µL reaction). Provided minor input to experimental design; and minor edits and inputs to the figures and manuscript.
Given less input on experimental design and less edits and input on the figures and script.
REAL-TIME KINETICS AND MELT CURVES IN SINGLE- MOLECULE DIGITAL LAMP DIFFERENTIATE SPECIFIC AND
NONSPECIFIC AMPLIFICATION EVENTS TO IMPROVE THE LIMIT OF DETECTION
For Bst 3.0, although there was considerable overlap, we again observed that nonspecific amplification tended to have slower peak rates than specific amplification (Fig 3.3I). Furthermore, the maximal rate of nonspecific amplification in Bst 2.0 tended to be lower than nonspecific amplification in Bst 3.0 (50 and 75 RFU/30 sec, respectively). Consequently, the degree of overlap of specific and nonspecific amplification was greater for Bst 3.0 than Bst 2.0.
The shear number of non-specific amplification events is much lower for Bst 2.0 than for Bst 3.0. Partitions in panels a, c, d, g, h, k, n using Bst 2.0 are rendered at 20% opacity in NTC and 20% opacity in the presence of template. Panels b,e,f,I,j,n using Bst 3.0 are rendered at 5% opacity in NTC and 20% opacity in the presence of template.
However, unlike Bst 3.0, there are far fewer nonspecific amplification events and their presence does not affect LOD. Plots showing cumulative counts of true positive amplification (dashed blue), false positive counts (dashed red), and incorrectly identified partitions (dashed black). m) Plot of LOD curves as a function of time, comparing Bst 2.0 (solid blue with Tm, dashed blue without Tm) and Bst 3.0 (solid red with Tm, dashed red without Tm). We observed for both Bst 2.0 and Bst 3.0 enzymes that specific and nonspecific amplification were qualitatively similar, independent of background DNA concentration.
Furthermore, both the nonspecific amplification events at high melting temperature and low melting temperature were greater for Bst 3.0 than for Bst 2.0. For Bst 2.0, we observed consistent nonspecific amplification at high and low Tm, regardless of the concentration of gDNA. At low background rates, such as when using Bst 2.0, there is inherent variability in the false positive fraction, which can impact the LOD.
SURFACTANT-ENHANCED DNA ACCESSIBILITY TO NUCLEASE ACCELERATES PHENOTYPIC Β-LACTAM ANTIBIOTIC
SUSCEPTIBILITY TESTING OF N. GONORRHOEAE 1
The nuc-aAST method measures differences in the accessibility of genomic DNA to an exogenous nuclease between control and treated samples after a short exposure to antibiotics (ABX). We observed a significant difference in the percentage of accessibility between susceptible and resistant isolates after 90 minutes of exposure. Two penicillin-susceptible (PEN-S) and two penicillin-resistant (PEN-R) Ng isolates were exposed to penicillin in the presence of DNase I.
Checkmarks indicate enhancers that meet our criteria for inclusion in nuc-aAST; X's indicate amplifiers that did not meet our criteria. We then hypothesized that the differences observed in the extent of response of susceptible isolates after 15 minutes of exposure to each antibiotic, including the errors observed in CFM and CRO testing (open points, Figure 4.4b,c), could be the result of differences in how rapidly any β-lactam affects Ng(72). The samples were then transferred to the amplification step and incubated for 5 min in the presence of CHAPS.
NA concentrations were used to determine percent accessibility once the measured NA concentrations in the sensitized sample became significantly different between control and treated chips. The Cq values obtained by qPCR are used to calculate percent accessibility and percent lysis as described in the equations below. Template concentrations are used to calculate percent accessibility and percent lysis as described in the equations below.
Working cultures were prepared, exposed to ABX, and enhancement steps were performed as described for the CHAPS enhancement step i. Treated samples in the initial exposure step had a final concentration of 1.0 µg/mL PEN, CFM, or CRO. Degree, Impact of population structure in the design of RNA-based diagnostics for antibiotic resistance in Neisseria gonorrhoeae.
HIGH-MOLECULAR-WEIGHT POLYMERS FROM DIETARY FIBER DRIVE AGGREGATION OF PARTICULATES IN THE MURINE
SMALL INTESTINE
We then placed the PEG-coated particles into the SI luminal fluid with a volume fraction of ≈0.001. We therefore first attempted to quantify the physical properties of the polymers in the luminal fluid of the SI. We can use this crossover to estimate the size of the minima in the interparticle potentials for the three PEG solutions (Figure 5.4H).
The magnitude of the minimum of the interparticle potential (Umin/kT) plotted against the polymer concentration for the three PEG solutions in (D). Our measurements of pH throughout the SI suggest that it is possible that MUC2 precipitates out in the upper. We find that these estimates suggest that there are some differences in the polymeric composition of the SI of these two groups.
We then generated serial dilutions of the samples and found different aggregation thresholds for the samples (Figure 5.S3C-D). We therefore wanted to test the hypothesis that immunoglobulins promote aggregation of PEG-coated particles in the SI. To test the strength of the aggregation effect in the different samples, we serially diluted the samples and compared the volume-weighted mean aggregate sizes at each dilution (Figure 5.6C and D).
These estimates suggest that there are some differences in the polymeric composition of the SI of these two groups of mice. When we made serial dilutions of the samples, we found that the accumulation levels were similar (Figure 5.S6C and D). Dietary polymers control aggregation of PEG-coated particles in a consistent manner with depletion-type interactions.
The estimates also suggest that there are differences in the polymeric composition of the SI of the two groups. This work shows that even PEG-coated particles, which have minimal biochemical interactions, form aggregates in the luminal fluid of the SI.
QUANTITATIVE AND QUALITATIVE CHANGES IN THE UPPER GASTROINTESTINAL MICROBIOME CONTROLLED BY SELF-
AND HOST PHYSIOLOGY
