Cell Biology

Multiplexed whole-animal imaging with reversibly switchable optoacoustic proteins – Science Advances

INTRODUCTION

Photo- or optoacoustic (OA) imaging combines optical contrast with ultrasound resolution, enabling high-resolution, real-time in vivo imaging well beyond the 1-mm penetration depth typical of microscopy methods (1, 2). OA has already provided intriguing insights into tumor heterogeneity (3), neuronal dynamics (4), psoriasis (5), and brown fat metabolism (6) based on endogenous contrast from hemoglobin and lipids (7, 8). This is complemented by theranostic research (9, 10) and clinical application (11), e.g., imaging of Crohns disease (12). However, OA imaging has not yet become a routine tool in life sciences because of the lack of strong OA contrast agents that can be expressed in desired cell types (13). The few transgenic labels used in OA so far (8) give weak signals that cannot rise above the strong background due to hemoglobin. Photochromic proteins that can be reversibly switched between two states by light can overcome this limitation by entirely separating the label signal, which modulates in accordance with the illumination, from the background, which remains constant (14). This concept, despite being validated in several studies (1520), has not been implemented widely because it requires complex instrumentation and data analysis tools. Here, we introduce two reversibly switchable OA proteins (rsOAPs) and demonstrate their use with widely accessible off-the-shelf commercial imaging systems as well as our open-access machine learning (ML)based software code for analysis. One of our new rsOAPs shows high switching speeds and dynamic range of photomodulation that allow us to resolve the signals of different cell populations labeled with differentiable rsOAPs in close proximity in the same animal, demonstrating the potential for simultaneous tracking of different cellular processes through temporal multiplexing.

(A) Homology model (iTasser, based on 6g1y) of ReBphP-PCM. Truncation sides indicated. (B) Schematic representation of truncations. (C) Photoinduced differential spectra for truncations. (D and E) Similar representations for RpBphP1. (F) Stabilization of the BV D-ring in RpBphP1 and DrBphP. (G) Similar representation for PaBphP, which shows an arginine similar to ReBphP, presumably abstracting D194 and destabilizing the Pfr state, yielding a faster photoswitching.

Bacterial photoreceptors called bacteriophytochromes (BphPs) (21) have emerged as most suitable for rsOAP development due to their strong absorption in the near-infrared range and low photofatigue (22). To identify the most promising candidate for further development, we screened eight native BphPs (table S1) and selected the one from Rhizobium etli. A set of truncations enabled us to minimize its size and optimize its photoswitching characteristics. In brief, on the basis of existing structural data as well as homology models, we created truncations containing the minimum PAS-GAF-PHY photosensory core domains [photosensory core module (PCM)] together with extra amino acids from the annotated linkers between PHY and histidine kinase domains and tested their characteristics in regard to signal generation and photoswitching (Fig. 1, A to E, and note S1). The final variant ReBphP-PCM shows twofold larger change in OA signal (Fig. 2G), more than fivefold faster switching (Fig. 2, C and D), and greater resistance to photofatigue than other rsOAPs (Fig. 2E), while its high molar absorbance is on par with the recently described Deinococcus radiodurans DrBphP-PCM (92,000 M1 cm1; Fig. 2, B and G) (19). Those characteristics enable higher numbers of switching cycles per second, which improves sensitivity and allows imaging over longer timeframes. On the molecular level, this acceleration of switching speed is the result of a less stabilized Pfr state favoring the photoinduced transition to Pr. The destabilization is likely caused by an arginine present in ReBphP but not in RpBphP1 and DrBphP. This arginine, by interacting with a conserved aspartate, which, in turn, interacts with the D-ring of the Pfr state chromophore, weakens Pfr stabilization (Fig. 1, F and G, and note S1).

(A) Principle of photoswitching in BphPs (top) and concept of temporal unmixing of two labels (green ball and blue star; bottom). Illumination shown in dark red (780 nm) and red (630 nm). Pr refers to the red state, while Pfr refers to the far-red state. The bottom part of the panel was adapted with permission from (14). (B) Absorbance spectra of Pr and Pfr states of the three rsOAPs in comparison to hemoglobin (HbO2 and Hb, 1999, S. Prahl, omlc.org). (C) Switching cycles of the rsOAPs. Only OA signal at 770 nm is shown. a.u., arbitrary units. (D) Single switching cycle from (C), shown with an exponential fit. (E) Photofatigue of the proteins per cycle. (F) Absorbance ratio between the Pfr and Pr state for different wavelengths. (G) Absorbance (filled bars) and OA signal intensity (hollow) ratio between the Pfr and Pr state for the three rsOAPs at 770 nm. (H) Matthews coefficient shown as a function of number of cycles and pulses. Shown is the analysis of a 4T1 tumor expressing ReBphP-PCM; histology was used as ground truth. All proteins have been adjusted to equal Soret peak absorption.

Our truncation strategy also proved successful in obtaining a switchable RpBphP1-PCM from Rhodopseudomonas palustris, in contrast to a previous report that truncated forms of this protein do not undergo reversible switching (19). Our engineered RpBphP1-PCM maintains the far-red state (Pfr) extinction coefficient and photochromic behavior of the parental RpBphP1 (Figs. 1E and 2B and fig. S1), and the change in its OA signal following illumination at 770 nm is similar to that of the previously described DrBphP-PCM (Fig. 2G). (Plasmid for expressing ReBphP-PCM in bacteria and eukaryotic cells or for introduction into viral vectors can be obtained from Addgene.) Both new rsOAPs are monomeric (fig. S2) and show higher expression in mammalian cells than the full-length parental proteins (fig. S3). The two developed rsOAPs and DrBphP-PCM show distinctive switching speeds, which is the reason for our ability to discriminate the proteins in vivo successfully. As a result, probes expressed in different cells in close proximity in the animal can be distinguished during high-resolution OA imaging.

We performed all OA imaging using an off-the-shelf, commercially available multispectral OA tomography device with a 10-Hz pulsed tunable laser and a 256-element transducer array (MSOT, iThera Medical). Off-switching of rsOAPs was achieved with light at 770 nm, which gave the highest difference in OA signal intensity between the on and off states (fig. S5A), while on switching was achieved using light at 680 nm. Lower wavelengths did not substantially improve the transition to the on state (fig. S5B). The number of laser pulses per wavelength was chosen to cover the full switching kinetics, but it can be significantly reduced using information-content analysis, which allows an estimate of the minimal number of cycles and pulses per cycle required to discern the labeled structure, thus effectively limiting imaging dwell time, which is essential for, e.g., time-resolved studies (Fig. 2H, fig. S6, and note S2). All temporal unmixing was conducted with in-house code developed to analyze time-varying patterns in the reconstructed data in the frequency and time domains using classic ML approaches (Fig. 3, Materials and Methods, and notes S3 and S4). In brief, after running fluence and motion correction on the data, a range of distinctive features was extracted from the photomodulated signal for each voxel of the tomography images. On the basis of a set of these data and corresponding histology as ground truth, a bagged random forest algorithm (23) was trained and validated on independent datasets of a different type to prevent overfitting. The ensuing model was then used to analyze all data in this study. The code for data preparation, for analysis with the model used in this work, and for generation of new models is available to the community along with graphical user interfaces.

The time-varying patterns in the OA raw data are extracted in the Feature calculation (blue) and analyzed using a classification model in the Data analysis step (yellow). In Model building (green), a classification model is trained based on imaging data with associated histology ground truth. In the script, two algorithms can be selected: bagged tree or support vector machine. For uniformity, the images shown in this work exclusively use the bagged tree approach, although the support vector machine has some virtues (note S4).

The OA imaging scheme is shown in Fig. 4A. First, we used rsOAPs for superficial in vivo imaging. We imaged the development of 4T1 mouse mammary gland tumors coexpressing ReBphP-PCM and green fluorescent protein (GFP) after they were grafted onto the backs of FoxN1 nude mice (n = 3). The initial population of 0.8 106 injected cells was readily visualized separate from all background absorbers (Fig. 4B), as was the growing tumor mass at all days after injection (fig. S7, A to D). To test whether this imaging is also possible in brain tissue after light passes through the skull, we implanted 0.7 106 4T1 cells coexpressing ReBphP-PCM and GFP at a depth of 3.6 mm and imaged them immediately thereafter. Comparison of the OA images with fluorescence images obtained after sacrificing mice revealed perfect overlap of the labeling, confirming background-free identification of 1.4 105 cells deep in the mouse brain (Fig. 4C). Next, we used the same rsOAP to image deep-seated tumors of HCT116 human colon carcinoma cells implanted intraperitoneally (n = 2). From day 3 onward, we were able to visualize the growth of several individual tumor sites to a depth of ~1 cm (fig. S7, E and F). Comparison of OA images and histology obtained after sacrifice confirmed identification of all malignant tissue (Fig. 4, D to F, and fig. S7, E and G), including small tumors or metastatic patches containing less than 10,000 cells (fig. S7, I and J).

In certain experiments, GFP was coexpressed to allow fluorescence imaging of histology slices. (A) Schematic of OA tomography used in this work. (B) 4T1 cells (0.8 106 injected subcutaneously) stably expressing ReBphP-PCM and imaged on day 9. (C) 4T1 cells (0.7 106 injected intracranially) stably expressing ReBphP-PCM imaged at a depth of 3.6 mm in the brain (arrow I) immediately after injection. (D) Volume representation of HCT116 cells (1.5 106 injected intraperitoneally) stably expressing ReBphP-PCM at consecutive time points. (E) Histology of the same mouse at day 14. (D and E) Arrows indicate distinctive tumor masses. (F) Certainty of prediction (weighted sum of tree scores) indicating quality of discerning label signal or background of regions of interest shown in (E) (right). (G) Imaging of the indicated concentrations of Jurkat T cells in Matrigel expressing ReBphP-PCM immediately after subcutaneous implantation; because of the polymerization process, no homogeneity is expected. (H) Imaging of the indicated concentrations of E. coli expressing ReBphP-PCM in Matrigel immediately after subcutaneous implantation. In (B), (C), (G), and (H), color maps refer to R2 (detection quality). All slices are single representative slices. All scale bars, 1 mm. Earlier time points and data from additional mice can be found in fig. S7.

To assess the sensitivity of imaging with our rsOAPs, we imaged dorsal implants of Matrigel containing different numbers of Jurkat T lymphocytes stably coexpressing ReBphP-PCM and GFP in mice (Fig. 4G). We detected populations as small as 500 cells/l, suggesting the potential for sensitive tracking of immune processes. Similarly, imaging of dorsal implants of Matrigel containing bacteria expressing ReBphP-PCM detected populations as small as 14,000 bacteria/l (Fig. 4H). This sensitivity may be useful for studying and optimizing bacteria-based tumor therapies (24).

A strong advantage of photocontrollable labels is the possibility to delineate multiple labels based on their individual switching kinetics. To demonstrate this, we imaged 1-mm alginate beads filled with Escherichia coli expressing ReBphP-PCM, RpBphP1-PCM, or DrBphP-PCM. All beads were unambiguously identified on the basis of their switching kinetics (Fig. 5A). The same differentiation was achieved in vivo after implanting Jurkat T lymphocytes expressing ReBphP-PCM or DrBphP1-PCM and E. coli expressing RpBphP1-PCM into the back of mice (Fig. 5B).

(A) Imaging of an alginate bead phantom containing E. coli expressing rsOAPs ReBphP-PCM, RpBphP1-PCM, and DrBphP-PCM. (B) Imaging of Jurkat T cells and E. coli (1.4 106) expressing each of the three rsOAPs imaged immediately after implantation into a 4T1 tumor. (C) Imaging of a 4T1 tumor with implants of two Jurkat T cells expressing rsOAPs. Zones of mixture of the two populations with distinct kinetics are colored yellow. In (A) to (E), color maps indicate clusters showing distinguishable kinetics. (D) Imaging of a 4T1 tumor stably expressing ReBphP-PCM at day 9 (arrows II and III) imaged immediately after E. coli (108 cells) expressing DrBphP-PCM have been injected into the tumor (arrow I). Histology confirmation is inferred from fluorescence in DrBphP-PCM (Cy5 only) and ReBphP-PCM (GFP primarily). (E) Volume representation of k. All slices are single representative slices. All scale bars, 1 mm.

Because the kinetics of photoswitching are energy dependent, fluence changes due to light attenuation by surrounding absorbersphotochromic or staticcomplicates temporal multiplexing (note S5). Thus, one aim of our development of the fast-switching ReBphP-PCM was to achieve a switching time constant clearly separate from other rsOAPs. We show that 4T1 tumor expressing ReBphP-PCM and GFP are readily distinguished from infiltrating DrBphP-PCMexpressing E. coli cells (intratumorally injected 108 bacteria; Fig. 5, D and E). This means that multiplexing is possible for co-registration studies and that the concentrations of the labels can be estimated based on the convoluted kinetics (fig. S8). Similarly, we show this for two populations of rsOAP labeled Jurkat T lymphocytes in a 4T1 tumor (intratumorally injected 5 105 cells; Fig. 5C). Hence, temporally unmixed multiplexed OA imaging of cells of the immune system enables following their function and involvement in disease mechanism in vivo, longitudinal on the organism level.

The combination of OA and transgenic rsOAP labels allows the tracking of specific cell populations in vivo, which can open up possibilities for longitudinal studies of intact animals in diverse fields such as immunology, developmental biology, neurology, and cancer research. To support these studies, we describe next-generation rsOAPs that provide faster switching and greater resistance to photofatigue than existing rsOAPs, allowing highly sensitive detection, and importantly true multiplexing, without interference from hemoglobin or other abundant absorbers in vivo. These rsOAPs can be used with off-the-shelf equipment and our ML-based open-access image processing code to detect populations of fewer than 500 cells in vivo. The approach relies entirely on a time series of images, thus making the concept translatable between different OA imaging devices. These tools will facilitate the wider use of OA imaging in life sciences, particularly for the study of cellular dynamics and interactions on the level of whole organisms.

RpBphP1 (16) was obtained from Addgene (V. Verkhusha, plasmid no. 79845). Mammalian optimized ReBphP was synthesized as gene strings (GeneArt, Life Technologies, Regensburg, Germany). All other BphPs used in the study have been a gift from A. Mglich (University of Bayreuth, Germany).

For bacterial protein expression, the coding sequences of all BphPs used in the study except RpBphP1 were polymerase chain reaction (PCR)amplified as a Nde I/Xho I fragment and cloned into the second multiple cloning site of the pET-Duet1 vector (Novagen, Merck Millipore). RpBphP1 was PCR-amplified as a Nde I/Pac I fragment and cloned into the second multiple cloning site of the pET-Duet1 vector. In addition, for biliverdin synthesis, the heme oxygenase (HO) of Nostoc sp. was cloned using Nco I/Hind III into the first multiple cloning site of pET-Duet1.

For equimolar mammalian expression, first, ReBphP_P2A and mCherry were PCR-amplified and then stitched using overlap PCR as an Eco RI/Xba I fragment and cloned in a pcDNA3.0 vector (Thermo Fisher Scientific). Later similar constructs for other BphPs were made by amplifying them as Eco RI/Not I fragment and inserted in place of ReBphP1-PCM in the above construct. The resulting plasmids allowed the equimolar coexpression of RpBphP1, RpBphP1-PCM, ReBphP-PCM, ReBphP-PCM, or DrBphP-PCM and mCherry proteins.

Proteins have been expressed in E. coli strain BL21 (DE3) (New England Biolabs, #C2527). In brief, plasmids expressing BphPs and HO were transformed into the BL21 host cells. Bacterial cells were grown in LB media supplemented with ampicillin at 37C until the culture reached OD (optical density) 0.6, followed by induction of protein expression by addition of IPTG (isopropyl--d-thiogalactopyranoside) and further incubation for 16 to 18 hours at 22C. The next day, the bacterial pellet was collected by centrifugation and pellet was resuspended in phosphate-buffered saline (PBS). After cell lysis, proteins were purified by immobilized metal affinity chromatography in PBS, followed by gel filtration on a HiLoad 26/600 Superdex 75 pg (GE Healthcare Life Sciences, Freiburg, Germany).

For absorption spectra, the purification buffer was exchanged against PBS and the proteins were measured with a Shimadzu UV-1800 spectrophotometer (Shimadzu Inc., Kyoto, Japan) using a 100-l quartz cuvette. To measure the ON (Pfr) and OFF (Pr) spectra of respective proteins, photoswitching was carried out using 650/20-nm or 780/20-nm light-emitting diodes (Thorlabs) placed above the quartz cuvette in the spectrophotometer.

Fluorescence measurements for all BphPs were performed with a Cary Eclipse Fluorescence spectrophotometer (Varian Inc., Australia). Photoswitching was carried out as above. Fluorescence measurement was done by fixing excitation wavelength at 700 nm and emission wavelength at 720 nm. Excitation wavelength and emission slit were set to 5 nm, and the absorbance at the excitation wavelength was always equal to 0.1 to avoid inner filter effects.

4T1 and Jurkat cells were maintained in RPMI 1640. HeLa and HCT116 cells were maintained in Dulbeccos modified Eagles medium (DMEM) and McCoy 5A medium, respectively. All media were supplemented with 10% fetal bovine serum (Invitrogen) and antibiotics [penicillin (100 U/ml) and streptomycin (100 mg/ml)]. Cells were cultivated at 37C and 5% CO2.

Tissue culture. The Platinum-E and RD114 packaging cell lines were cultivated in cDMEM (Complete Dulbeccos modified Eagle medium), HCT116 cell line was grown in McCoy 5A medium (Life Technologies), and 4T1 and Jurkat cells were cultured in cRPMI (Complete Roswell Park Memorial Institute)1640 Medium. All media were supplemented with 10% fetal calf serum, 0.025% l-glutamine, 0.1% Hepes, 0.001% gentamicin, and 0.002% streptomycin.

Generation of constructs. ReBphP-PCM-IRES-GFP was amplified using specific primers (5-ATTAGCGGCCGCGCCACCATGAGCGGCACCAGAG-3 and 5-ATTAGAATTCTCACTTGTACAGCTCGTCCATGCCGTGAGTG-3) and cloned into the mP71 using Not I and Eco RI restriction sites. The mP71 vector was a gift from W. Uckert.

Generation of cell lines. For retrovirus production, Platinum-E or RD114 packaging cells were transfected with the retroviral vector mP71-ReBphP-PCM-IRES-GFP using calcium phosphate precipitation. The supernatant of the packing cells was collected at 48 and 72 hours after transfection and purified from the remaining cells by centrifugation at 1500 rpm at 4C for 7 min. One day before transduction, nontissue culturetreated 48-well plates were coated with RetroNectin (Clontech) according to the manufacturers recommendations overnight at 4C. After washing once with PBS, virus supernatant was added and centrifuged at 3000g and 32C for 2 hours. Virus supernatant was removed, and cell lines (4T1, HCT116, and Jurkat) were added in 400 l of the respective medium supplemented with 1:100 LentiBOOST Solution A and 1:100 LentiBOOST Solution B (Sirion Biotech). Cells were then spinoculated at 800g at 32C for 1.5 hours. After 5 days of culture, cells were sorted for high expression of GFP using flow cytometry.

All animal experiments were approved by the government of Upper Bavaria and were carried out in accordance with the approved guidelines. For 4T1 xenografts of stably expressing ReBphp-PCM and GFP, 0.8 106 cells in PBS have been implanted in the back of FoxN1 nude mice (Charles River Laboratories, Boston, USA) and maintained for 9 days. For HCT116 cells expressing ReBphP-PCM and GFP, 1.5 106 cells in 200 l PBS have been injected intraperitoneally in FoxN1 nude mice and were maintained for 14 days. For intracranial injections of stably expressing ReBphP-PCM and GFP 4T1 cells, mice were first anesthetized according to the animal protocol. The head of the mouse was fixed in a Stereotaxic frame (David Kopf Instruments, model 940), an incision in the skin was made using a scalpel, and a small hole was drilled into the skull. Later, 5-l cells (0.14 106 cells/l) were injected slowly with a 10-l Hamilton syringe (26Gs). The incision in the skin was closed using Histoacryl (B. Braun Melsungen AG). The mice were scanned in MSOT and sacrificed immediately after scanning. For Matrigel implants of Jurkat cells expressing ReBphP-PCM, different concentrations of cells ranging from 6400 to 500 cells/l were implanted subcutaneously in the back of the mice. Similarly, bacterial cells expressing ReBphP-PCM in different concentrations (1.4 105 to 1.4 104 cells/l) were also implanted in the back of the mice. For multiplexing experiment, bacterial cells expressing rsOAPs individually with the concentration of 1.4 106 cells/l were implanted on the back of the mice in the same plane. For multiplexing experiment in vivo, intratumoral injections, bacterial cells expressing DrBphP-PCM resuspended in PBS have been injected into the 4T1 tumor expressing ReBphP-PCM and GFP using an insulin syringe with a 30-gauge needle.

For all MSOT imaging, mice have been anesthetized using 2% isoflurane in O2. Anesthetized mice were placed in the MSOT holder using ultrasound gel and water as coupling media. After termination of the experiments, all mice have been sacrificed and stored at 80C for cryosectioning.

Phantom and mice data were acquired using a commercially available MSOT scanner (MSOT In Vision 256-TF, iThera Medical GmbH, Munich, Germany). In brief, nanosecond pulsed light was generated from a tunable optical parametric oscillator (OPO) laser and delivered to the sample through a ring-type fiber bundle. The wavelengths, 680 and 770 nm, were used for photoswitching and imaging in phantoms and in mice. Light absorbed by the sample generates an acoustic signal that propagates through the sample and is detected outside the sample by a cylindrically focused 256-element transducer. The transducer array had a central frequency of 5 MHz (6 dB was approximately 90%) with a radius of curvature of 40 mm and an angular coverage of 270. Acoustic signals were detected as time series pressure readouts at 2030 discrete time points at 40 MS/s (Mega-samples per second). The acquired acoustic data were reconstructed using the ViewMSOT version 3.8.1.04 (iThera Medical GmbH, Munich, Germany) software with the following settings: 50 kHz to 6.5 MHz; trim speed of 7.

All data analysis was conducted using MATLAB2018b. The data reconstructed with ViewMSOT were loaded into MATLAB by iThera MATLAB code (iThera MATLAB, version: msotlib_beta_rev75). All analyses were carried out with the code provided along with this manuscript (note S3). In brief, movement correction was done by phase correlation preliminary to optimization-based image co-registration with the intensity and nonrigid co-registration of frames of the first cycle being used as reference. For further processing, different features of the time series have been computed and are used for classification/switching label detection using an ML model. For fast Fourier transform, repetitive frequency of the whole concatenated signal for each image point is computed to identify signals corresponding to the illumination schedule. For exponential fitting, the normalized mean kinetic of all cycles is used. Then, the coefficients compared to an expected exponential kinetic are calculated and used as a quality measure. Here, positive and negative exponential are considered. Using fit coefficients and quality of fit (R2) as measures, only 77% accuracy compared to a ground truth is achieved. Thus, additional features are invoked. Overall, all analyzed features are (i and ii) the coefficient for the exponential fit (exp(b(x + 1)) and exp(b(x 1) + 1) of the mean kinetic (mean of all cycles); (iii) R2 of the fit; (iv) the mean intensity over the concatenated signal; (v) max-min of all the data at the pixel; (vi to ix) median maximums and minimums of cycles along with SD; (x) number of cycles with positive or negative trend; (xi) the length of the part of the cycle that shows a trend, i.e., at what point the signal vanishes in the noise; and (xii) Fourier coefficient for the expected frequency defined by the photocontrol schedule. All those are used as predictor values for an unmixing model based on random forest approaches (23, 25)for overall model, trained on 4T1 day 9 as well as highest concentration of Jurkat T lymphocytes. We used 50 trees in the ensemble, as further increase of number did not lead to out-of-bag error decrease. This approach resulted in model performance increase up to 96% of positive predictive value for ground truth (see note S4 for more details on the use of ML in this work).

For visualization, data were not further processed and are shown against the respective slice at 680 nm as anatomy information, except in the case of 4T1 injected in brain where the anatomy is shown at 900 nm. Representative slices are shown. For clustering, appropriate ranges of the kinetic parameter were chosen on the unmixed data to distinguish different labels.

After sacrificing, the mice were cryopreserved at 80C. To detect the fluorescence in tumors, the respective part of the mouse was embedded in Tissue-Tek O.C.T. (Sakura Finetek Europe B.V., Zoeterwonde, The Netherlands). Sections (10 m) were cut (Leica CM1950, Leica Microsystems, Wetzlar, Germany) for brain, 4T1, and HCT116 mice at the interval of 150, 250, and 500 m, respectively, and imaged using a 482/35-nm bandpass for excitation and 535/38-nm bandpass filter for detection of GFP fluorescence. Images were taken using an Andor LucaR charge-coupled device camera (DL-604M, Andor Technology, Belfast, UK) with 10-s exposure and a gain of 10. On the basis of the histology, ground truth on co-registered images was created using a semiautomatic procedure based on anatomical markers and intensity-based multimodal co-registration together with a nonrigid spline-based method and human (two independent)based selection of signals in the fluorescence images.

A 2 to 4% (w/v) aqueous solution of sodium alginate was prepared in PBS. E. coli strain BL21 cells expressing rsOAPs were harvested by centrifugation (4000 rpm, 20 min) and resuspended in PBS. The cell suspensions were then mixed with sterile alginate. Beads were formed by filling the alginate cell mixtures in the syringe with 30-gauge needle, followed by centrifugation at 300 rpm, which allowed the addition of the mixtures into sterile CaCl2 (200 mM). The cell-containing beads, 1 mm in diameter, were allowed to solidify for 10 min before CaCl2 was replaced by fresh distilled water. The cell beads were then randomly distributed in the agar phantom with 1.5% (w/w) agar and 3.5% (v/v) intralipid emulsion and imaged in MSOT as described elsewhere.

For OA characterization of rsOAPs, custom-made experimental setup was used as described earlier (22). Briefly, nanosecond excitation pulses were generated by an OPO laser (SpitLight DPSS 250 ZHGOPO, InnoLas) running at a repetition rate of 50 Hz. Constant pulse energy was ensured using a half-wave plate in a motorized rotation stage (PRM1Z8, Thorlabs) and a polarizing beam splitter; using a lookup table and adapting the polarization with the half-wave plate, we kept the power constant at 1.3 mJ (otherwise mentioned) over the whole illumination schedule. Samples were injected into an acoustically coupled flow chip (-Slide I 0.2 Luer, hydrophobic, uncoated, ibidi) and illuminated from one side using a fiber bundle (CeramOptec) at a constant pulse energy of 1.3 mJ at the fiber output. Photoswitching was carried out by illuminating the sample alternatively with 650- and 780-nm light. OA signals were detected with a cylindrically focused single-element transducer (V382-SU, 3.5 MHz, Olympus) followed by signal amplification by 60 dB with a wide-band voltage amplifier (DHPVA-100, Femto) and digitized at 100 MS/s with a data acquisition card (RZE-002 400, GaGe). Dependency of Pfr Pr conversion on 770-nm pulse energy was measured with different pulse energies (0.4, 0.7, 1.0, and 1.3 mJ). Dependency of Pfr Pr conversion on repetition rate of laser was measured with three different laser repetition rates (10, 25, and 50 Hz). Effect of different switching ON wavelength and resulting dynamic range at 770 nm was measured using different switching ON wavelength ranging from 630 to 680 nm.

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Multiplexed whole-animal imaging with reversibly switchable optoacoustic proteins - Science Advances

Genetics

Global Genetic Testing Market Forecasts for Applications and Technologies 2020-2024, Updated in Light of Impact of COVID-19 Pandemic -…

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Global Genetic Testing Market Forecasts for Applications and Technologies 2020-2024, Updated in Light of Impact of COVID-19 Pandemic -...

Genetics

IGS Providing Tools to Help Ranchers With Cattle Genetics – – RFD-TV

"Beef breeds, historically, haven't always worked together so well, or so much, but IGS broke the mold on that," states the CEO of Red Angus Association of America, Tom Brink, "being able to combine these data sets, more analytical power, better EPD prediction to use for all breeds involved, IGS really facilitates that in an unprecedented way."

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IGS Providing Tools to Help Ranchers With Cattle Genetics - - RFD-TV

Genetics

When Cancer Cells Cant Make Their Own Fat, They Eat Whats Around Them – SciTechDaily

A switch in cancer fat metabolism from production to import could be exploited for therapy, researchers say. Credit: National Institutes of Healthy Public LIbrary

Cancer cells rewire their metabolism to compensate for a halt in fat production by importing more fat molecules from their environment.

Knowing what cancer will do next could lessen the likelihood of it becoming resistant to treatment. A new U of T study investigates how cancer adapts its metabolism to potentially overcome therapies still in development.

Several clinical trials have failed because metabolism is such an adaptive process by which cancer cells gain drug resistance, says Michael Aregger, a co-lead author and Research Associate working with Jason Moffat, Professor of molecular genetics in the Donnelly Centre for Cellular and Biomolecular Research, who co-led the work. If you know how cells are able to adapt to perturbations, maybe we can target them more specifically to avoid resistance from developing.

If you know how cells are able to adapt to perturbations, maybe we can target them more specifically to avoid resistance from developing Michael Aregger, Research Associate

The research was also led by Brenda Andrews and Charles Boone, University Professor and Professor of molecular genetics at the Donnelly Centre, respectively, and Chad Myers, a Professor of computer science at the University of Minnesota-Twin Cities.

The study, published this week in the journal Nature Metabolism, is the first to investigate global changes in cancerous cells as they adapt to a shortfall of critical nutrients such as fat molecules, or lipids, which make up the cells outer envelope.

When cancer cells are unable to make their own lipids, they gobble them up from their environment to ensure a steady supply of these essential building blocks, the study found. Lipids also serve as fuel and chemical signals for communication between cells, among other roles.

The switch in metabolism could be bad news for drugmakers seeking to target cancer by reducing its lipid reserves. In particular, drugs that inhibit an enzyme called FASN, for fatty acid synthase, involved in an early step of lipid synthesis, are being explored in patient trials. Fatty acids are precursors of larger lipid molecules and their production is increased in many cancers thanks to elevated FASN levels, which are also associated with poor patient prognosis.

The U of T study suggests that the effectiveness of FASN inhibitors could be short-lived owing to cancers ability to find another way to procure lipids.

Because FASN is upregulated in many cancers, fatty acid synthesis is one of the most promising metabolic pathways to target says Keith Lawson, a co-lead author and PhD student in Moffats lab enrolled in the Surgeon-Scientist Program at the Faculty of Medicine. Given that we know there is a lot of plasticity in metabolic processes, we wanted to identify and predict ways in which cancer cells can potentially overcome the inhibition of lipid synthesis.

To block fatty acid synthesis, the researchers employed a human cell line from which the FASN coding gene was removed. Using the genome editing tool CRISPR, they deleted from these cells all ~18,000 or so human genes, one by one, to find those that can compensate for the halt in lipid production. Such functional relationships are also referred to as genetic interactions.

Data analysis, performed by Maximilian Billmann, a co-lead author and a postdoctoral fellow in Myers lab at Minnesota-Twin Cities, revealed hundreds of genes that become essential when cells are starved of fat. Their protein products clustered into well-known metabolic pathways through which cells hoover up dietary cholesterol and other lipids from their surroundings.

Cells intake of cholesterol has become textbook knowledge since it was discovered half a century ago, winning a Nobel Prize and inspiring the blockbuster drug statin and many others. But the new study found that one component of this process remained overlooked all this time.

The gene encoding it was only known as C12orf49, named after its location on chromosome 12. The researchers re-named the gene LUR1, for lipid uptake regulator 1, and showed that it helps switch on a set of genes directly involved in lipid import.

This was a big surprise to us that we were able to identify a new component of the process we thought we knew everything about, says Aregger. It really highlights the power of our global genetic interaction approach that allowed us to identify a new player in lipid uptake in a completely unbiased way.

By a remarkable coincidence, two groups working independently in New York and Amsterdam also linked C12orf49 to lipid metabolism, lending further support for the genes role in this process. The New York team published their findings in the same journal issue as Moffat and colleagues.

Inhibiting LUR1, or other components of lipid import, along with FASN could lead to more effective cancer treatments. Such combination therapies are thought to be less susceptible to emerging drug resistance because the cells would have to simultaneously overcome two obstaclesblocked lipid production and importwhich has a lower probability of occurring.

Therapeutic context that comes out of our work is that you should be targeting lipid uptake in addition to targeting lipid synthesis and our work highlights some specific genes that could be candidates, says Lawson.

Reference: Systematic mapping of genetic interactions for de novo fatty acid synthesis identifies C12orf49 as a regulator of lipid metabolism by Michael Aregger, Keith A. Lawson, Maximillian Billmann, Michael Costanzo, Amy H. Y. Tong, Katherine Chan, Mahfuzur Rahman, Kevin R. Brown, Catherine Ross, Matej Usaj, Lucy Nedyalkova, Olga Sizova, Andrea Habsid, Judy Pawling, Zhen-Yuan Lin, Hala Abdouni, Cassandra J. Wong, Alexander Weiss, Patricia Mero, James W. Dennis, Anne-Claude Gingras, Chad L. Myers, Brenda J. Andrews, Charles Boone and Jason Moffat, 1 June 2020, Nature Metabolism.DOI: 10.1038/s42255-020-0211-z

The research was supported by the Canadian Institutes for Health Research, Ontario Research Fund, Canada Research Chairs Program and the U.S. National Institutes of Health.

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When Cancer Cells Cant Make Their Own Fat, They Eat Whats Around Them - SciTechDaily

Genetics

Is Applied Genetic Technologies (AGTC) Stock Outpacing Its Medical Peers This Year? – Yahoo Finance

Investors focused on the Medical space have likely heard of Applied Genetic Technologies (AGTC), but is the stock performing well in comparison to the rest of its sector peers? One simple way to answer this question is to take a look at the year-to-date performance of AGTC and the rest of the Medical group's stocks.

Applied Genetic Technologies is one of 888 companies in the Medical group. The Medical group currently sits at #1 within the Zacks Sector Rank. The Zacks Sector Rank considers 16 different groups, measuring the average Zacks Rank of the individual stocks within the sector to gauge the strength of each group.

The Zacks Rank is a proven system that emphasizes earnings estimates and estimate revisions, highlighting a variety of stocks that are displaying the right characteristics to beat the market over the next one to three months. AGTC is currently sporting a Zacks Rank of #2 (Buy).

Within the past quarter, the Zacks Consensus Estimate for AGTC's full-year earnings has moved 11.64% higher. This signals that analyst sentiment is improving and the stock's earnings outlook is more positive.

Our latest available data shows that AGTC has returned about 15.71% since the start of the calendar year. At the same time, Medical stocks have gained an average of 0.21%. This means that Applied Genetic Technologies is outperforming the sector as a whole this year.

Looking more specifically, AGTC belongs to the Medical - Biomedical and Genetics industry, which includes 382 individual stocks and currently sits at #34 in the Zacks Industry Rank. This group has gained an average of 8.10% so far this year, so AGTC is performing better in this area.

AGTC will likely be looking to continue its solid performance, so investors interested in Medical stocks should continue to pay close attention to the company.

Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free reportApplied Genetic Technologies Corporation (AGTC) : Free Stock Analysis ReportTo read this article on Zacks.com click here.Zacks Investment Research

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Is Applied Genetic Technologies (AGTC) Stock Outpacing Its Medical Peers This Year? - Yahoo Finance

Immunology

Ecoimmunology – Wikipedia

Ecoimmunology or Wild Immunology is an interdisciplinary field combining aspects of immunology with ecology, biology, physiology, and evolution. The field of ecoimmunology, while young, seeks to give an ultimate perspective for proximate mechanisms of immunology.

Classical, or mainstream, immunology works hard to control variation (inbred/domestic model organisms, parasite-free environments, etc.) and asks questions about mechanisms and functionality of the immune system using a reductionist method. Comparative immunology investigates the major changes of the immune system among taxa. While ecoimmunology originated from these fields, it is distinguished by its focus to describe and explain natural variation in immune functions,[1] and, more specifically, why and how biotic and abiotic factors contribute to variation in immunity in animals. Study of the trade-offs between immunity and other physiological mechanisms are a central study topic within the field, but have been expanded to include roles in species and individual variation, sex, social aspects, and mating system differences, and progress is also being made to develop methods to explore this variation.[2] Many studies involve in vivo laboratory experiments, but there have been recent calls for immunologists to study immune variation more in wild animals in particular.[3] Multiple institutes engage in ecoimmunological research, such as the Center for Immunity, Infection and Evolution at the University of Edinburgh and the Max Planck Institute for Immunoecology and Migration. The US National Science Foundation has funded a Research Coordination Network) to bring methodological and conceptual unity to the field of ecoimmunology.

The immune systemcan be regarded as diary of exposition to viruses. Migration of animals lead to different exposure to animals as virus hosts. Combination of migration routes where individuals might be exposed to virus hosts can be used to cross-validate anti-gens and anti-bodies detected in the immune system of e.g. in migratory animals. For some viral infections you can detect in an early phase of the infection antibodies of the Immunglobulin class M (IgM) and later in the infection the detection of antibodies of the Immunglobulin class G (IgG) recommended. This basic example shows, how the integration of different approaches:

One of the fields seminal papers, by Folstad and Karter,[4] was a response to Hamilton and Zuks famous paper on the handicap hypothesis for sexually selected traits.[5] Folstad and Karter proposed the immunocompetence handicap hypothesis, whereby testosterone acts as a mediator of immunosuppression and thus keeps sexually-selected traits honest.[4] Although there is only moderate observational or experimental evidence supporting this claim up until now, the paper itself was one of the first links to be made suggesting a cost to immunity requiring trade-offs between it and other physiological processes. In 1996, a foundational paper for the field invoked trade-offs, the allocation of limited resources among competing, costly physiological functions, as a prime cause of variation in immunity.[1] Evidence for these putative trade-offs has often proven to be elusive [6]

More recently, ecoimmunology has been the theme of three special issues in peer-reviewed journals, in Philosophical Transactions of the Royal Society B, in Functional Ecology, and in Physiological and Biochemical Zoology (see External links).

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Ecoimmunology - Wikipedia

Immunology

Could a global ‘observatory’ of blood help stop the next pandemic? – Science Magazine

The antibodies in blood samples from around the world could reveal where previously identified pathogens are popping up and where new ones are emerging.

By Robert BazellJun. 13, 2020 , 8:00 AM

Sciences COVID-19 reporting is supported by the Pulitzer Center.

Michael Mina is out for bloodmillions of samples, which a nascent effort dubbed the Global Immunological Observatory (GIO) would monitor for signs of pathogens spreading through the population. Instead of a telescope, it will rely on technology that can measure hundreds of thousands of distinct antibodies in a microliter of blood. If the GIO can overcome technical and logistical hurdles and find sustained funding, he says, it could provide a powerful tool for monitoring and responding to disease outbreaks.

For now, the idea is just a pilot project to track the spread of COVID-19. The stealthy spread of that disease through the population underscored the need for such a monitoring system, says Mina, an immunologist and epidemiologist at Brigham and Womens Hospital and the Harvard School of Public Health, who with colleagues outlines the GIO concept this week in eLife. (The co-authors include Jeremy Farrar, an infectious disease specialist and director of the Wellcome Trust, as well as vaccine and immunology specialists Adrian McDermott and Daniel Douek of the National Institutes of Health.)

Disease surveillance in the United States now relies on a patchwork of hospitals, clinics, and doctors to report unusual events to state health departments, which pass the information on to the Centers for Disease Control and Prevention (CDC). The need for faster, more comprehensive surveillance, Mina says, was starkly clear with the inability to identify and model local circulation of COVID-19 in a timely fashion.

Mina wants to watch for outbreaks by looking for antibodies to infectious agents in regularly collected, anonymized blood samples from every possible sourceblood banks, plasma collection centers, even the heel needle sticks of newborns, which are taken in most states from every baby in order to identify genetic diseases. The samples would be identified only by geographical area. Chip-based platforms that can identify hundreds of thousands of antibodies are already produced commercially by companies including VirScan and Luminex. Mina says these could easily be scaled up to look at huge numbers of samples, either individually or in batches

This is an extraordinary and exciting concept, says infectious disease specialist William Schaffner of the Vanderbilt University Medical Center. It is an example of the kind of fresh new thinking we need in public health. But, Schaffner adds, The logistical challenges for such an endeavor could be daunting.

Mina and his co-authors envision initially testing about 10,000 samples per day and later, if they secure funding to build up the project, some 100,000 per day for the United States alone. Even the smaller number would detectfar faster than the current reporting systeman outbreak of Zika virus in rural Louisiana, for example, or an eruption of West Nile virus in Colorado. The GIO could also accelerate the monitoring of seasonal influenza, allowing hospitals to prepare for possible surges and for public health officials to be sure vaccine is distributed as efficiently as possible.

When a new infectious disease such as COVID-19 appears, the GIO could track its spread. The antibody-detecting chips wouldnt necessarily have to be updated to spot a new pathogen, such as SARS-CoV-2, the cause of COVID-19. Researchers might see a rise in antibodies that nonspecifically target known pathogens--and might flag their unknown relatives. For example, a burst of antibodies that cross-react various coronaviruses would likely have been seen in people in Wuhan, China, who were infected with the novel coronavirus.

Antibodies, which typically appear 1 to 2 weeks after an infection starts, can signal not just people who are currently infected but also those who had the disease and recovered. The GIO would also identify the particular strains of a bacteria or virus infecting people because each produces a unique antibody signature.

The idea of regularly monitoring entire populations for antibodies arose in the lab of evolutionary biologist Bryan Grenfell at Princeton University, where Mina worked as a postdoctoral fellow. Now, Mina has joined Grenfell and Jessica Metcalf, also an evolutionary biologist at Princeton, in expanding the concept.

The GIO team is already building a pilot laboratory in Massachusetts, while it looks to secure financial support. Given the importance we believe this could have, we are beginning to look for funding from some of the major philanthropic donors of public health work, Mina says. We are currently exploring and open to all options.

Meanwhile, the team s pilot project, supported by the Open Philanthropy foundation, is gathering millions of anonymous blood samples from a plasma-collecting company Octapharma. By screening them for antibodies to SARS-CoV-2, Mina and his colleagues hope to learn how useful widespread antibody testing can be in tracing the spread of the new coronavirus and possibly predicting future hot spots or localized outbreaks.

People often do not develop antibodies until well after infections; for SARS-CoV-2 it takes 1 or 2 weeks. But Mina says the antibody testing still provides valuable information. A week into an outbreak isn't huge, he said. For example, if we were doing this with [blood from] just a small fraction of New York, we would have detected that [the SARS-CoV-2] was there in February and could have given [Governor Andrew] Cuomo plenty of ammunition to close down the city March 1 instead of March 19.

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Could a global 'observatory' of blood help stop the next pandemic? - Science Magazine

Immunology

Non-allergic asthma linked with increased risk of severe COVID-19 – HSPH News

However, study finds allergic asthma did not significantly increase the risk of severe illness

June 11, 2020Adults with asthma who became infected with the coronavirus that causes COVID-19 were at higher risk of developing severe illness compared with adults who did not have asthma, according to a new study led by researchers at Harvard T.H. Chan School of Public Health and Massachusetts General Hospital.

The study, the first to specifically examine the longitudinal relationship between asthma and risk of developing COVID-19, also showed that the risk was largely driven by non-allergic asthma. Allergy-induced asthma, according to the findings, did not significantly increase the risk of severe illness.

A pre-proof of the study was published online in The Journal of Allergy and Clinical Immunology on June 6, 2020.

Despite reasonable speculation that asthma could be a risk factor for severe COVID-19, rigorous, population-based research is needed to know whether asthma and its major subtypes actually increase risk, said Liming Liang, corresponding author of the study and associate professor of statistical genetics at Harvard Chan School. Based on these new findings, clinicians can improve risk-stratification and target COVID-19 prevention in patients with asthma, particularly those with non-allergic asthma.

Since the start of the pandemic, clinicians have suspected that patients with asthma have increased susceptibility to COVID-19, but no longitudinal studies have analyzed the actual risk. For the new study, the research team analyzed data from 492,768 participants in the UK Biobank, which stores biologic samples from participants and is linked to their medical records. The researchers found 65,677 participants had asthma and 641 patients had severe COVID-19.

After adjusting for age, sex, body mass index, and other factors, the researchers found that having non-allergic asthma increased the risk of severe COVID-19 by as much as 48%. They also found that the risk of severe COVID-19 increased by as much as 82% among people with asthma and chronic obstructive pulmonary disease. Importantly, however, the study showed that people with allergic asthma had no statistically significant association with severe COVID-19.

Zhaozhong Zhu, first author of the study and a research fellow at Harvard Chan School, noted that the new findings are consistent with recent studies that have shown low levels of receptors for novel coronavirus (SARS-CoV-2) on the airway cells of individuals with allergic diseases and asthma.

The findings are especially important amidst allergy season, said study co-author Kohei Hasegawa, a physician at Massachusetts General Hospitals Department of Emergency Medicine. This study should provide some reassurance during allergy season to the tens of millions of people with allergic asthma, Hasegawa said.

Funding for this study came from National Institutes of Health grant R01 AI-127507.

Association of asthma and its genetic predisposition with the risk of severe COVID-19, Zhaozhong Zhu, Kohei Hasegawa, Baoshan Ma, Michimasa Fujiogi, Carlos A. Camargo,and Liming Liang, The Journal of Allergy and Clinical Immunology, June 6, 2020, doi: https://doi.org/10.1016/j.jaci.2020.06.001

Chris Sweeney

Photo: iStock

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Non-allergic asthma linked with increased risk of severe COVID-19 - HSPH News

Immunology

Some Forms of Common Cold May Give COVID-19 Immunity Lasting up to 17 Years, New Research Suggests – Science Times

Immunology experts recently released a paper suggesting that coronavirus immunity might be possible through a different genetic pattern of SARS, or the common cold. They claim that this possible immunity may last up to 17 years.

Coronavirus related symptoms that mimic the common cold, called betacoronavirus, may either have immunity or be infected by a milder form of the virus. Betacoronaviruses, specifically OC43 and HKU1, are the cause of common colds as well as severe chest infections, leaving the young and elderly in critical conditions.

The beta virus has similar genetic features with its SARS family, such as COVID-19 and Middle East Respiratory Syndrome (MERS). If an individual had been previously exposed to the common cold, the body develops memory T cells, which become a defense system when a similar infection enters the body, resulting in immunity.

T cells, a type of white blood cell, is a prominent part of the immune system, adjusting the body to respond to specific attacking pathogens. Because of their ability to create lasting shields against viruses, they are called 'memory cells.'

Professor Antonio Bertoletti, an immunologist from the Duke-NUS Medical School in Singapore, and his team have new findings on the function of T cells amidst the global pandemic. They discovered that patients who survived the SARS lung virus in 2003 had immune responses to COVID-19 antibodies.

'These findings demonstrate that virus-specific memory T cells induced by betacoronavirus infection are long-lasting, which supports the notion that COVID-19 patients would develop long-term T cell immunity,' said the team. 'Our findings also raise the intriguing possibility that infection with related viruses can also protect from or modify the pathology caused by SARS-Cov-2 [the strain of coronavirus that causes COVID-19].'

Four blood samples were taken from coronavirus patients who had recovered, 23 who has SARS, and 18 individuals who had exposed to neither deadly viruses.

What surprised Bertoletti's team was that 50% of unexposed patients had defensive T-cells which could defend their immune system against the betacoronaviruses SARS and COVID-19. Most likely, the scientists concluded, their immunity developed memory cells from obtaining common colds caused by betacoronavirus or other unknown pathogens.

In another study of T cell immunity, virologist Angela Rasmussen of Columbia University agrees with the Singaporean team. Alongside Shane Crotty and Alessandro Sette, immunologists at the La Jolla Institute for Immunology, bioinformatic tools were used to predict which viral protein fragments would trigger the strongest T cell responses.

Read Also: First American to Receive Placental Cell Treatment For COVID-19 is an Acclaimed Broadway Scenic Designer

Ten recovered patients were exposed to the immune cells where their 'helper T cells...recognized the SARS-CoV-2 spike protein.' 'The immune system sees this virus and mounts an effective immune response,' said Sette. Rasmussen said, 'these papers are really helpful because they start to define the T cell component of the immune response.'

New insight on adaptive immunity against coronavirus antibodies is the key to developing a 'vaccine design and evaluation of candidate vaccines,' notes Bertoletti's study. Moreover, understanding more about immunity today will be important for 'epidemiological model calibration of future' pandemics and social distancing measures.

Read Also:Italy Nears Herd Immunity As Over Half of Its Covid-19 Epicenter's Population Tested Positive for Antibodies

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Some Forms of Common Cold May Give COVID-19 Immunity Lasting up to 17 Years, New Research Suggests - Science Times

Immunology

State and Centre trying hard, but didnt spread awareness about community risk – Hindustan Times

As the state hit the one lakh mark for Covid-19 cases on Friday, Dr Satyajit Rath, retired scientist from Delhi-based National Institute of Immunology, and currently adjunct professor at the Indian Institute of Science Education and Research, Pune, spoke on factors behind the rise in Covid-19 cases, states handling of the outbreak and public health care system. Excerpts:

What are the factors responsible for the large number of Covid-19 cases in Maharashtra and Mumbai?

Globally, much of Sars-CoV-2 transmission seems to be direct, meaning from being in close proximity to an infected person. Since the entry of the infection into India is from overseas, it is quite unsurprising that the high-volume international entry points, Mumbai and Delhi, have had most seeding of local outbreaks. When that is coupled with crowded urban conditions, especially in Mumbai, again, the number and size of local outbreaks are unsurprising, as also the outcome that infection has spread to surrounding areas (western Maharashtra, Gurgaon) from these initial seeding points. These are not really huge numbers, given the numbers some other countries with early high-volume outbreaks have had and continue to have. The pandemic is going to be with us in fits and starts for a long time.

Has the state done enough to contain the epidemic?

The state (the Centre and Maharashtra government) is trying hard, and with good intentions, and acknowledges and tries to act on evidence-based directions and approaches needed (unlike the government leaderships in the two countries ahead of India Brazil and the USA). It also acknowledges some of its own limitations and shortcomings.

And the inadequacies?

The state has failed to address the core issue, which is to build a community partnership in which there is clarity about the fact that the pandemic is not so much an individually lethal risk as a community risk. The result is stigmatisation, ostracisation, fear and concealment, disruption of non-Covid-related health services and their usage (childrens vaccinations, other non-pandemic illness handling, et cetera), and the like. The state has not built robust and generous public support structures for the underprivileged anywhere near the extent needed.

What is your assessment of the public health infrastructure?

The state (the Centre and Maharashtra government), most directly, have not yet acknowledged the sad state of public health care systems, especially at community level. It is a contributor to the quantitatively inadequate pandemic response. As a simple example, the general consensus globally is that for efficient community-based Covid-19 case identification and contact tracing, one skilled and trained health worker will be needed per three thousand people. This kind and level of manpower in neighbourhoods, backed up with infrastructure, data handling, and testing-technical capacity, was not available before the pandemic, has not been aimed at so far, and is not being built for the future.

Data shows that the state has been carrying out about 14,000 tests everyday as against the testing capacity of 38,000. Its a similar case with Mumbai too. Should we be testing more?

Given these numbers, it is quite likely that larger numbers of testing would help; more tests will still likely identify more cases. However, a major issue has come to be; how easy is it to get tested, and how clear, supportive and unthreatening are the practical decision streams for what is to be done if the test comes positive and how it is to be done?

What has been the consequence of constant changes in testing criteria by Indian Council for Medical Research (ICMR)?

The major consequence is that it becomes difficult if not impossible to compare data from testing under one set of criteria with data from testing under another set. This makes it hard to say anything much about the trajectory of the epidemic in the country. However, it is also true that ICMR has had to work in practical constraints of test and related resource (swabs, transport) availability, and of changing case numbers.

How do you gauge the potential impact following the easing of lockdown restrictions in Maharashtra/Mumbai?

It is quite likely that numbers will go up with a delay of a week or two, especially because there is no cultural assimilation in the community of the need for physical distancing (not social distancing; we need social solidarity). Case numbers are most likely to go up, not in some orderly and well-distributed fashion, but as increasing numbers of local, scattered outbreaks.

Suggestions to control further spread of the infection and revive the economy range from a ban on gathering of more than two or five people, enforcement of a stringent containment strategy and cyclical lockdown. Your comments.

A single strategy wont work everywhere, all the time. All of these and more are likely to be invoked and used, in reactive fashion, in different local situations at different times. It would be helpful if some systematic analytical thought has been given to identifying which local circumstances would warrant which of these containment approaches; I do not know if governments are doing this kind of planning.

What is the takeaway, three months into the pandemic?

Unless we persuade ourselves, culturally, as a community, that physical distancing and social solidarity need to become the new normal, and unless we re-commit ourselves, as a representative government, to the idea of major, long-term, durable investment in comprehensive public health systems as a core responsibility of governance, the outcomes of the pandemic are likely to be bleak for us.

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State and Centre trying hard, but didnt spread awareness about community risk - Hindustan Times