extfieldsofstudy:
Materials Science
Medicine

s2fieldsofstudy: Biology Chemistry

text:
Biocompatible near-infrared fluorescent nanoparticles for macro and microscopic in vivo functional bioimaging.

Near-infrared (NIR) imaging technology has been widely used for biomedical research and applications, since it can achieve deep penetration in biological tissues due to less absorption and scattering of NIR light. In our research, polymer nanoparticles with NIR fluorophores doped were synthesized. The morphology, absorption/emission features and chemical stability of the fluorescent nanoparticles were characterized, separately. NIR fluorescent nanoparticles were then utilized as bright optical probes for macro in vivo imaging of mice, including sentinel lymph node (SLN) mapping, as well as distribution and excretion monitoring of nanoparticles in animal body. Furthermore, we applied the NIR fluorescent nanoparticles in in vivo microscopic bioimaging via a confocal microscope. Under the 635 nm-CW excitation, the blood vessel architecture in the ear and the brain of mice, which were administered with nanoparticles, was visualized very clearly. The imaging depth of our one-photon microscopy, which was assisted with NIR fluorescent nanoprobes, can reach as deep as 500 μm. Our experiments show that NIR fluorescent nanoparticles have great potentials in various deep-tissue imaging applications.

Introduction
Fluorescence imaging technique occupies an important and unique position in life sciences and medicine [1], due to its advantages for noninvasive study of biological tissues. In addition, fluorescence imaging can provide high spatial resolution [2][3][4][5] and high sensitivity [6] of samples. However, the realization of higher resolution is at the expense of short penetration depth in biological tissues [7]. Absorption of biological tissue and water, as well as scattering, limits the focusing capability, and penetration depth of light. To overcome this problem, lots of studies have mainly focused on developing fluorophores in the "optical transmission window" of biological tissue (700 -900 nm) during past years [8]. Compared with visible light, NIR light is less absorbed/scattered by biological tissue and water, and then has deeper tissue focusing and penetration capability. Furthermore, autofluorescence can be also effectively restrained when NIR light is adopted as an excitation source. Thus, NIR imaging technology is a promising tool for deep-tissue in vivo biomedical study [9,10].
Recently, various NIR luminescent nanoparticles have already been applied in biological imaging, such as quantum dots (QDs) [11,12], up-conversion nanoparticles (UCNPs) [13]. QDs possess many advantages: high brightness, good photostability, tunable absorption and emission spectra and a broad spectral excitation range [14,15]. Some NIR QDs composed of heavy metals (e.g. PbSe, PbS and CdTe) have certain cytotoxicity [16,17], which makes them not so suitable for biological imaging. However, some research has been done to synthesize new types of QDs, which are more biocompatible and less harmful to biological cells and tissues, facilitating their applications in deep-tissue bioimaging [18][19][20]. UCNPs are also widely used in biological imaging [21,22]. Although the luminescent quantum yield of most UCNPs is very low [23], they still provide many advantages for bioimaging applications, such as high signal to noise ratio, superior photostability, tunable luminescence spectrum, as well as sharp absorption and emission lines [24]. Due to facile synthesis process, relatively high fluorescence quantum yield, and convenient chemical modification, organic NIR fluorophores are still the most promising candidates in biomedical imaging area [25]. Unfortunately, most NIR fluorophores cannot be directly used for biological applications, since they are hydrophobic. Many efforts are being made to solve this problem. One way is introducing some hydrophilic groups to the hydrophobic fluorophores to make them aqueously soluble [26]. However, aggregation of fluorophores still occurs when they are injected into animal body. Another promising alternative approach is using aqueously dispersable nanoparticles to encapsulate hydrophobic fluorophores [27], which can overcome the aggregation of fluorophores very effectively. Among various nanoparticles, polymer nanoparticles made up of biocompatible hydrophobic-hydrophilic copolymers (e.g. phospholipids-PEG), are very promising and more suitable for in vivo applications [28]. They can be facilely synthesized and conjugated with biomolecules to target certain parts of live animal body (e.g. tumors) [29,30]. They have little cytotoxicity and good biocompatibility [31]. The long PEG chains in polymer nanoparticles can improve the long-time circulation of nanoparticles in an animal body and help to avoid capture/degradation by reticuloendothelial systems (RES).
For deep-tissue in vivo microscopy, multi-photon fluorescence microscopy is a very good solution. Relying on the absorption of two or more NIR photons by fluorophores at once, multiphoton microscopy is capable of achieving better focusing, deeper tissue penetration and efficient light detection noninvasively. It has been widely used in thick-tissue and in vivo bioimaging [32,33]. However, multi-photon fluorescence is a typical nonlinear optical effect, and high peak power excitation is essential for multi-photon microscopy, which may cause overheating and damage towards biological tissues. In addition, most high peak power pulsed laser sources (e.g. femtosecond laser) are very expensive and sensitive to the working environment, and cannot be easily afforded. In some cases, one-photon confocal microscopy with red light excitation and NIR emission can be another good way to achieve deep-tissue bioimaging. Red excitation light (e.g. 635 nm) is near the "optical transmission window" of biological tissue (700 -900 nm). Optical absorption and scattering of red light in biological tissue is not distinct, and its penetration in tissues can be also deep. Furthermore, laser sources for one-photon fluorescence excitation (e.g. 635 nm CW laser) are very safe to bio-samples. They are cost effective, stable in various experimental environments, and easily afforded. In addition, the quantum yield of IR fluorophore under one-photon excitation is usually larger than 0.01 [31], but the quantum yield of some very efficient visible dyes under two-photon excitation is usually less than 10 −8 [23]. It illustrates IR fluorophore under one-photon excitation has higher fluorescence efficiency, which is helpful to obtain strong imaging signals.
In this paper, IR-820, which is a typical type of NIR fluorophore, was encapsulated in polymer nanoparticles. The morphology of IR-820 doped polymer nanoparticles was characterized. The absorption and fluorescence spectra of the nanoparticles were measured, and their chemical stability was also verified. For macro in vivo bioimaging, IR-820 doped polymer nanoparticles were intradermally injected into the forepaw of nude mice for SLN mapping. In addition, they were intravenously injected into live mice via their tail vein, and the whole-body NIR imaging results illustrated that polymer nanoparticles could be excreted from mice body through their hepatobiliary transport. For microscopic in vivo bioimaging, mice were also intravenously administered with NIR fluorescent nanoparticles, and all the experiments were performed on a confocal microscope with 635 nm-CW excitation. The blood vessels at various vertical depths in the ear of a BABL/c mouse were observed with high signal to noise ratio. Furthermore, we performed microscopic in vivo imaging of the brain of mice. Three-dimensional (3D) reconstructive images of blood architecture were achieved, and the imaging depth of our one-photon confocal microscopy, which was assisted with NIR fluorescent nanoprobes, could reach as deep as 500 μm. The in vivo bioimaging results demonstrated that NIR fluorophores doped polymer nanoparticles can be utilized as a good candidate for high-contrast and deep-tissue functional bioimaging.  Figure 1 shows the synthesis procedures of IR-820 doped polymer nanoparticles. Typically, 800 μl of IR-820 in ethanol (1 mM) was mixed with 3.2 ml of DSPE-mPEG 5000 in chloroform (10 mg/mL). The mixture was sonicated for two minutes to form a homogeneous solution, and dried at 70 °C in a rotary evaporator. Next, 500 μl of phosphate buffered saline (PBS, 1X, pH = 7.4) was added into the obtained lipidic film, and the solution was sonicated for five minutes. After that, an optically clear suspension containing IR-820 doped polymer nanoparticles was obtained, which can be used for further experiments.

Characterization
The structure of IR-820 doped polymer nanoparticles was taken by a JEOL JEM-1230 transmission electron microscopy (TEM) operated at 80 kV in bright field mode. The absorption spectra of nanoparticles were characterized by a Shimadzu 2550 UV-vis scanning spectrophotometer (400 -900 nm). NIR fluorescence spectra of nanoparticles were characterized by a Maestro in vivo optical imaging system (CRI, Inc. Woburn, MA), which consists of an optical head, an optical coupler, a cooled scientific-grade monochrome CCD camera and an image acquisition/analysis software.

Cell viability analysis
The cytotoxicity of IR-820 doped polymer nanoparticles to HeLa cells was evaluated by following the instructions of cell counting kit-8 (CCK-8). 5000 cells/well in a 100 μl suspension were incubated in 96-well plates for 24 h. Then, a 100 μl fresh culture medium containing nanoparticles with various concentrations ranging from 0 to 4 μg/ml was added into each well. After incubation for 24 h, the culture medium was removed and the cell well was washed thrice with PBS. In the end, 100 μl culture medium containing CCK-8 (10%) was added into each well for 2 h, and the absorbance was measured at 450 nm by using a microplate reader (Thermo, USA).

Histology
The short-term toxicity of IR-820 doped polymer nanoparticles was evaluated through histological analysis evaluations. 24 h after the intravenous injection of 300 μl nanoparticles (1 mg/mL in 1X PBS, which is also the concentration of nanoparticles we used for the following in vivo imaging) and (only)1X PBS (as control), mice with and without treatment (as another control) were sacrificed, and their major organs (heart, liver, kidney and spleen) were removed. Tissues were fixed in 10% formalin, embedded in paraffin, sectioned, and stained with hematoxylin and eosin. The histological sections were imaged under an inverted optical microscope for analysis.

Macro in vivo imaging studies
All in vivo experiments were performed in compliance with Zhejiang University Animal Study Committee's requirements for the care and use of laboratory animals in research. 18-21 g female nude mice were used for macro in vivo imaging studies. IR-820 doped polymer nanoparticles in PBS (1X, pH = 7.4) were intradermally injected into the left forepaw of a sedated nude mouse to perform SLN mapping. In addition, nude mice were administered with 300 μl of nanoparticles via tail vein injection and anesthetized with pentobarbital at various time points after the injection for whole-body functional bioimaging. All the NIR imaging was performed under the aforementioned Maestro in vivo optical imaging system.

Microscopic imaging of tissue-equivalent phantom
The synthesis of nanoparticle doped phantom is as following. 0.4 g of gelatin was added to 4 ml of DI water at 60 °C, and 100 μl of IR-820 doped polymer nanoparticles was added into the solution after the gelatin was totally dissolved by vigorous magnetic stirring. It was transferred to a dish, and kept at 4 °C for 2 h. A cylindrical solid-state phantom was then ready for imaging. A control group (without the adding of IR-820 doped polymer nanoparticles) was also prepared, accordingly. The phantoms were then imaged with an upright laser scanning confocal microscope under the 635 nm-CW laser excitation. The average power of excitation light after the water-immersed objective (20X, NA = 1, Olympus) was about 1.3 mW. The confocal aperture (C.A, the size of confocal pinhole) and the scan speed were set to 358 μm and 10 μs/pixel (512 X 512 pixels per frame), respectively.

Microscopic in vivo imaging studies
8-week-aged female BALB/c mice were then used for microscopic in vivo imaging. They were intravenously injected with 300 μl of IR-820 doped polymer nanoparticles via their tail vein. The upright laser scanning confocal microscope (635 nm-laser excited) was adopted for the microscopic imaging of blood vessels in the mouse ear, as well as blood vasculature in the mouse brain. For ear imaging, the average power of the excitation laser after the water-immersed objective (20X, NA = 1, Olympus) was about 1 mW. The C.A was set to 344 μm. The scan speed was set to 2 μs/pixel (512 X 512 pixels per frame). For brain imaging, the nanoparticles treated mice were anesthetized with pentobarbital, and the skulls of the mice were opened up through microsurgery. A metal ring with a handle was mounted onto the mouse brain. A round thin cover glass slide was then embedded in the metal ring and directly adhered to the mouse brain through dental cement. We make sure the brain was flattened by the cover glass slide, which is helpful to improve the microscopic imaging quality. The metal ring was then connected to a metal plate with a handle, via handle-handle fix. Since the metal plate was very heavy, this configuration could keep the mouse's head immobilized during the whole imaging process. Water was smeared between a long work distance (2 mm) water-immersed objective (20X, NA = 1, Olympus) and the top of the cover slide surrounded by the metal ring. The C.A of the confocal microscope was set to 600 μm, and the scan speed was set to 2 μs/pixel (512 X 512 pixels per frame). Figure 2(a) shows a typical TEM picture of IR-820 doped polymer nanoparticles. Since the electron quantities of the atoms constituting polymer nanoparticles and IR-820 molecule, are not very large, the contrast of the image is not high and the contour of the polymer nanoparticles is not very clear [34]. However, we could still discriminate the nanoparticles from the background, and they were indicated by circles in the TEM picture. The nanoparticles have a spherical morphology with an average size of ~45 nm. To verify IR-820 molecules have been encapsulated in the polymer nanoparticles, a drop of ethanol solution of IR-820 and a drop of aqueous solution of IR-820 doped polymer nanoparticles were slowly evaporated on a glass slide. After dried, they were directly imaged with the Maestro in vivo optical imaging system as mentioned, and the excitation wavelength was 704 nm. The fluorescence signal was extracted by a long-pass filter, which could also cut off the residual excitation light. A liquid-crystal tunable filter was automatically tuned from 740 nm to 900 nm with 10 nm increments, and the fluorescence intensity and image at each wavelength were recorded by the cooled monochrome CCD camera. As shown in Fig. 2(b), the fluorescence from the aggregates of IR-820 doped polymer nanoparticles could be clearly observed, and it was much brighter than that from the aggregates of IR-820 powder (could hardly be observed), from which we know that the IR-820 molecules have been efficiently encapsulated in the polymer nanoparticles. Otherwise, the fluorescence from the aggregates of the IR-820 doped polymer nanoparticles should be as weak as that from the aggregates of IR-820 powder, which was attributed to a phenomenon called "aggregation caused quench" (ACQ) [35]. Furthermore, the experimental results illustrated hydrophilic polymeric coating could protect hydrophobic IR-820 against denaturalization induced by the environment (e.g. oxidation), making the entire nanoparticles optically stable. The normalized linear absorption spectra of IR-820 in ethanol solution and aqueous solution of IR-820 doped polymer nanoparticles are shown in Fig. 2(c). The absorption peak wavelength (831 nm) of IR-820 doped polymer nanoparticles (in water) has about 7 nm red-shift compared with that (824 nm) of (only)-IR-820 (in ethanol). In addition to optical properties, chemical stability of NIR fluorophores is also very important, which can greatly affect their successful applications in in vivo animal studies. In our experiment, UV-vis absorption spectra of IR-820 doped polymer nanoparticles in PBS (1X, pH = 7.4) were monitored to evaluate their stability at different time points (0 h, 24 h, and 48 h). As shown in Fig. 2(d), the absorption spectra of nanoparticles kept very well in saline solution even after 24 h and 48 h, and the optical density of their peak wavelength also did not decrease distinctly, indicating aggregation of the nanoparticles did not occur, and they could keep chemically stable in saline solution for long time. Figure 2(e) shows the fluorescence spectra of IR-820 in ethanol solution and aqueous solution of IR-820 doped polymer nanoparticles, which were measured with the aforementioned Maestro in vivo optical imaging system under the 704 nm excitation. Both of the samples show a fluorescence peak wavelength around 860 nm. The fluorescence signal of IR-820 doped polymer nanoparticles mainly located in the "optical transmission window" of biological tissue (700 -900 nm), which demonstrates that the NIR fluorescent nanoparticles have the deep-tissue imaging potentials. The quantum yield of IR-820 doped polymer nanoparticles was measured by using a methanol solution of indocyanine green dye (fluorescence quantum yield of 0.12 [36]) as a reference, and was found to be 0.05 (not low for NIR nanoparticles). We further did a fluorescence stability test of IR-820 doped polymer nanoparticles under continuous light illumination. As shown in Fig. 2(f), even excited by 704 nm-light (from the aforementioned Maestro in vivo optical imaging system) for half an hour, the fluorescence intensity of nanoparticles was still higher than 85% of the original intensity. The photobleaching was negligible after the long time excitation, indicating IR-820 doped polymer nanoparticles possess stable fluorescence properties, which is very useful for long time dynamic bio-imaging.

Toxicity of IR-820 doped polymer nanoparticles
Figure 3(a) shows the relative viabilities of HeLa cells treated with IR-820 doped polymer nanoparticles after 24 h. The cells treated with nanoparticles maintained very high viabilities, and it was still larger than 95% even when the concentration of polymer nanoparticles was as high as 4 μg/ml. Furthermore, a histopathology examination shows that there was no inflammation or abnormalities of the major organs ( Fig. 3(b)) during the accumulation of IR-820 doped polymer nanoparticles via the blood circulation 24 h post-administration, suggesting that the nanoparticles are very biocompatible. The low cytotoxicity and high biocompatibility of IR-820 doped polymer nanoparticles make them as a good candidate for various in vivo bio-imaging applications.

IR-820 doped polymer nanoparticles for SLN mapping of nude mice
Accurate identification and biopsy of SLN are very significant in medicine. Some nanoparticles [37][38][39] (e.g. QDs and gold nanoparticles) have already been used for SLN mapping, and we present another approach in this work. 50 μl of IR-820 doped polymer nanoparticles in PBS (1X, pH = 7.4) was injected intradermally into the left forepaw of nude mice, and the mice were imaged with the in vivo optical imaging system under the 704 nm excitation. The NIR fluorescence signals from IR-820 doped polymer nanoparticles were colored in red and the background autofluorescence from mice body was colored in green (as shown in Fig. 4(a)-4(f)). An image of a typical mouse before injection (as a reference) was shown in the inset of Fig.  4(h), and only autofluorescence could be observed. Some NIR fluorescence signals appeared in the SLN site of the mouse 5 mins post sample treatment (Fig. 4(a)), due to the rapid diffusion of nanoparticles from the injection to lymphatics. As the time went by, the intensity of signals became stronger in the SLN site ( Fig. 4(b) and 4(c)), and the maximum of the signals intensity appeared after 60 mins (Fig. 4(c)). After that, NIR fluorescence signals decreased gradually (Fig. 4(d)-4(f)), because nanoparticles migrated from the SLN after 60 mins. Figure 4(h) shows the changes of NIR signal intensity of nanoparticles in the SLN site, which was consistent with our previously reported measure of this process by using other nanoparticles [32,34]. Furthermore, the fluorescence spectrum obtained from the SLN site ( Fig. 4(g)) verified that the NIR fluorescence signals were indeed emitted from IR-820 doped polymer nanoparticles. The results demonstrated that IR-820 doped polymer nanoparticles can be used as NIR optical probes for SLN mapping of live animals.

IR-820 doped polymer nanoparticles for whole-body functional bioimaging
To verify the capacity of IR-820 doped polymer nanoparticles in NIR whole-body in vivo imaging, 0.3 ml of nanoparticles in PBS (1X, pH = 7.4) was intravenously injected into a nude mouse. Another nude mouse without any treatment was used as a control. The two mice were then anesthetized with pentobarbital at various time points after the injection, and the sedated animals were imaged using the aforementioned Maestro in vivo optical imaging system. Figure  5(a)-5(f) show the NIR fluorescence imaging of the treated mouse (the right one) and the untreated mouse (the left one) at various time points of post-injection. Based on the imaging results and data treatment, the NIR fluorescence signals (with peak wavelength at 860 nm) from IR-820 doped polymer nanoparticles were colored in red and the background autofluorescence (e.g. from skin) was colored in green. Their normalized spectra could be distinguished from each other very easily (shown in Fig. 5(g)), which indicated the NIR in vivo imaging has very high contrast. One hour after the sample treatment, intense NIR fluorescence signals appeared in the liver of the treated mouse, and nanoparticles have already accumulated in the liver through blood circulation. As time went by, the intensity of the signals in the liver decreased gradually, indicating the mouse was metabolizing the nanoparticles all the time. Interestingly, 23 h post the sample treatment, NIR signals could be observed in the intestinal tract of the treated mouse, illustrating nanoparticles were excreted from the mouse body through its hepatobiliary transport. 120 h post the sample treatment, no NIR signals could be observed from the treated mouse, and most nanoparticles have been cleared from the mouse body. The background fluorescence of the reference mouse and nanoparticles treated mouse was different. One possible reason is that the intensity distribution of excitation light on the two mice was slightly different. Since the CCD detector in the Maestro in vivo optical imaging system was very sensitive, the slight difference was magnified, which made the background fluorescence of the two mice seem different. It is worth noting that both liver and intestinal tract were deep in the mouse body, and NIR fluorescent nanoparticles demonstrated their capacity in deep-tissue optical bioimaging. 80 days after the injection of the nanoparticles, no apparent pathological differences in shape, weight, eating, drinking, exploratory behavior or activity were observed between the two mice (with and without sample treatment). The results indicated the IR-820 doped polymer nanoparticles have very little toxicity, which may facilitate their clinical applications in disease diagnosis and therapy.  Laser assisted microscopy provides higher spatial resolution than macro imaging, but its imaging depth is not comparable with that of macro imaging. Tissue-equivalent phantom experiments were preformed to verify that IR-820 doped polymer nanoparticles have the capacity of deep-tissue microscopic imaging. Figure 6(a)-6(d) show the fluorescence images at different depths of the nanoparticle-doped-phantom, and their reconstructed 3D image is shown in Fig. 6(i), from which we know that the maximal microscopic imaging depth of NIR fluorescent nanoparticles in phantom is ~1100 μm. As for the control phantom, no fluorescence signals could be observed at any depth of the phantom, under the excitation of 635 nm-CW laser (shown in Fig. 6(e)-6(h)). The experimental results demonstrated that IR-820 doped polymer nanoparticles could be further used for microscopic imaging of thick tissues, as well as small animals.

Study of deep microscopic imaging capacity of IR-820 doped polymer nanoparticles in phantom
3.6 IR-820 doped polymer nanoparticles for in vivo microscopic imaging of blood vessels in a mouse ear IR-820 doped polymer nanoparticles were then utilized as NIR optical nanoprobes for in vivo microscopic imaging. Figure 7(a)-7(g) show the fluorescence images of blood vessels in the ear of the mouse at various vertical depths. Due to bright NIR fluorescence of IR-820, as well as low background autofluorescence of tissue under red light-excitation, the signal to noise ratio of all the images was very high, and the structure of blood vessels at any depth of the mouse ear could be observed very clearly. Figure 7(h) shows the corresponding reconstructed 3D image (taken with 2 μm depth increments) of the NIR fluorescent nanoparticles in the blood vessels, from which the vascular architecture in the mouse ear was vividly revealed.

IR-820 doped polymer nanoparticles for in vivo microscopic imaging of blood vasculature in a mouse brain
We further performed in vivo brain imaging of 8 week-female BALB/c mice by using IR-820 doped polymer nanoparticles. Figure 8(a)-8(l) show the fluorescence images of blood vasculature in the brain of the mouse at various vertical depths (below the skull). At the surface of the brain, the average power of the 635 nm-laser after the objective is ~0.8 mW, which is high enough to excite the NIR fluorescent nanoparticles in the blood vasculature. The brightest NIR signal occurred at the vertical depth of 130 μm. With the increasing depth in the mouse brain, the fluorescence signal intensity of IR-820 doped polymer nanoparticles decreased due to scattering and water absorption of the tissue (shown in Fig. 8(d)-8(l)). However, at the depth of 500 μm, the tiny structure of capillary vessels could still be discriminated by virtue of NIR fluorescence from the nanoparticles inside, and the average power of the 635 nm-laser after the objective is ~1.5 mW, which was very safe to the biosamples. Figure 8(m) and 8(n) show reconstructed 3D images (taken with 2 μm depth increments) of IR-820 doped polymer nanoparticles in the blood vasculature, from which we know that the maximal imaging depth could reach ~500 μm. In a traditional (one-photon) confocal microscopy with UV/blue/green excitation, the imaging depth is very difficult to be deeper than 100 μm. As aforementioned, with the help of less absorption/scattering of red light excitation and NIR emission light in the tissue, deeper imaging capability is achieved in our work, by directly utilizing one-photon confocal microscopy. By improving excitation and detection modes (e.g., making excitation wavelength get closer to the absorption peak of NIR fluorophore, and adopting NIR sensitive PMT to replace NIR insensitive PMT in the confocal microscope), as well as optical feature of fluorophores (e.g., increasing quantum efficiency), imaging depth of this one-photon confocal microscopy can be further increased, which will be very useful to some neurophotonics research and applications.

Conclusions
Optically and chemically stable polymer nanoparticles with NIR fluorophores doped were synthesized and utilized as efficient optical nanoprobes for macro/microscopic in vivo bioimaging. NIR fluorescent nanoparticles with very little toxicity can be used for SLN mapping and whole-body functional in vivo bioimaging. Furthermore, the NIR fluorescent nanoparticles were used for in vivo microscopic bioimaging via a confocal microscope with red excitation. The blood vessel architecture in the ear and the brain of mice, which were intravenously injected with nanoparticles, was revealed vividly. The imaging depth of our NIR nanoparticle-assisted one-photon microscopy can reach as deep as 500 μm. NIR fluorescent nanoparticles have great potentials in life sciences and medicine, such as early diagnosis/therapy of tumor.


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Aniline Is an Inducer, and Not a Precursor, for Indole Derivatives in Rubrivivax benzoatilyticus JA2

Rubrivivax benzoatilyticus JA2 and other anoxygenic photosynthetic bacteria produce indole derivatives when exposed to aniline, a xenobiotic compound. Though this phenomenon has been reported previously, the role of aniline in the production of indoles is still a biochemical riddle. The present study aims at understanding the specific role of aniline (as precursor or stimulator) in the production of indoles and elucidating the biochemical pathway of indoles in aniline-exposed cells by using stable isotope approaches. Metabolic profiling revealed tryptophan accumulation only in aniline exposed cells along with indole 3-acetic acid (IAA) and indole 3-aldehyde (IAld), the two major catabolites of tryptophan. Deuterium labelled aniline feeding studies revealed that aniline is not a precursor of indoles in strain JA2. Further, production of indoles only in aniline-exposed cells suggests that aniline is an indoles stimulator. In addition, production of indoles depended on the presence of a carbon source, and production enhanced when carbon sources were added to the culture. Isotope labelled fumarate feeding identified, fumarate as the precursor of indole, indicating de novo synthesis of indoles. Glyphosate (shikimate pathway inhibitor) inhibited the indoles production, accumulation of tryptophan, IAA and IAld indicating that indoles synthesis in strain JA2 occurs via the de novo shikimate pathway. The up-regulation of anthranilate synthase gene and induction of anthranilate synthase activity correlated well with tryptophan production in strain JA2. Induction of tryptophan aminotransferase and tryptophan 2-monooxygenase activities corroborated well with IAA levels, suggesting that tryptophan catabolism occurs simultaneously in aniline exposed cells. Our study demonstrates that aniline (stress) stimulates tryptophan/indoles synthesis via the shikimate pathway by possibly modulating the metabolic pathway.

Introduction
Aromatic compounds constitute the second most abundant class of organic compounds and are natural or anthropogenic. Since the industrial revolution, diverse array of aromatic chemicals has been synthesized and due to their extensive use, are continuously released into the environment [1,2]. Aromatic compounds are one of the major groups of xenobiotic compounds [3,4]. Many of these chemicals are persistent, toxic to life forms [2], and act as stressors [5,6]. Bacteria overcome these deleterious effects by employing various strategies, mainly active degradation/detoxification of these compounds. Some bacteria degrade these aromatic compounds for growth [4] and others transform these compounds to less toxic forms (detoxification) [7,8].
One such aromatic compound is aniline, a primary aromatic amine widely used in manufacturing of dyes, plastics, rubber additives, paints, herbicides, pesticides and in pharmaceutical industries [9]. Aniline is also formed by microbial transformation of nitroaromatic compounds and aniline based pesticides [10]. Owing to its extensive usage, large quantities of aniline is released into the environment by industrial effluents [9] and is accumulated in sediments, sludge and agricultural soil [10]. Aniline is considered as one of the important pollutants due to its recalcitrant properties [EEC, 1976;Federal Register, 1979) and is on the priority pollutant list of US Environmental Protection Agency [Federal Register, 1979). Aniline and its derivatives are known to be mutagenic, and their carcinogenicity has been reported in higher animals and mutagenecity in bacteria [11], hence its fate in the environment is of serious concern.
Metabolism of aniline and its derivatives by soil microorganisms was considered to be an effective measure for bioremediation [12]. Many aniline degrading bacteria were isolated from agricultural soils and industrial areas [9,10]; aerobic and anaerobic degradation pathways of aniline were also studied [4,9,13]. Biotransformation of aniline by soil microorganisms is one of the strategies of aniline detoxification [14,15]. Aniline and its derivatives were transformed to less toxic acetanilides by arylamine N-acetyltransfarase (NAT). NAT detoxifies aniline xenobiotics by transferring the acetyl group from acetyl-CoA to the nitrogen atom of arylamine [15]. Aniline transformation to formanilide by Nformylation and to aminophenol by hydroxylation was observed in some bacteria [16]. Transformation of aniline to anthranilate (a precursor of tryptophan) was reported in bacteria. Aniline was observed as major catabolite of diphenylamine, nitrodiphenylamine, and the formation of indole was also observed; the authors speculated that aniline was a possible precursor of indole [17].
Production of indole esters in the presence of aniline was also reported in a purple bacterium, Rhodobacter sphaeroides OU5, which, however, was dependent on the presence of a carbon substrate such as fumarate [18]. Similarly, production of tryptophan and other indole derivatives in the presence of aniline was reported in other purple bacteria [19] and these studies led to the speculation that aniline might be a precursor or an inducer for indole biosynthesis. However, this biochemical enigma has not been resolved so far. To address this question, we have employed stable isotopic and biochemical approaches to decipher the biosynthesis of indoles in aniline-exposed cells of a photosynthetic bacterium, Rubrivivax benzoatilyticus JA2. Our study demonstrated that aniline is not a precursor for indole biosynthesis; rather, it induces indole biosynthesis in strain JA2. Our results also suggest a possible stressinduced metabolic re-programming and shift towards synthesis of indoles in the presence of aniline.

Bacterial strain and culture conditions
Rubrivivax benzoatilyticus JA2 T (ATCC BBA-35) strain was used in this study. Strain JA2 was grown photoheterotrophically (anaerobic, 30uC; light 2,400 lux) in a mineral medium [20] supplemented with malate (22 mM) as the carbon source and ammonium chloride (7 mM) as the nitrogen source in fully filled screw cap test tubes (106100 mm) or reagent bottles (250 ml) at pH 6.8, 3061uC. Photoheterotrophically grown late-log phase culture (0.45 OD 660 nm ) of R. benzoatilyticus JA2 was used for all the experiments.
Effect of aniline on growth of strain JA2 was monitored by supplementing different concentrations of aniline (filter sterilized) to media and incubated under light at 30uC. Late log phase (OD 660 nm 0.4) culture was exposed to aniline (25 mM) and fumarate (13 mM) while the control received only fumarate. Aniline and control cultures were incubated under photoheterotrophic conditions for desired period (24 or 48 h); then cells were harvested and supernatant was used for total indoles estimation and extraction of metabolites. For studies with resting cell suspensions, late log phase culture (OD 660 nm 0.4) was harvested by centrifugation (10,0006g, 4uC, 10 min), washed twice with mineral medium (devoid of carbon and nitrogen sources) and finally suspended in the same mineral medium and exposed to aniline as described previously.
Effect of glyphosate on growth of strain JA2 during exposure to aniline/anthranilate was monitored by supplementing different concentrations of glyphosate (filter sterilized) to media. Growth restoration of strain JA2 (in presence of glyphosate) was performed by amending 1 mM of glyphosate to culture, after 20 h of incubation, the culture was supplemented with aromatic amino acids (150 mM of phenylalanine/tyrosine) or anthranilate (150 mM). Effect of glyphosate on indole production was monitored by supplementing 1 mM of glyphosate to culture during aniline/anthranilate exposure. Indoles were estimated by Salper's reagent using indole as standard [21].

Stable isotope precursor feeding
Late log phase (OD 660 nm 0.4) cultures of strain JA2 were supplemented with deuterium labeled aniline (Aniline-d 5 , 98 atom %D Sigma Aldrich) or fumarate (Fumaric acid-d 4 , 98 atom % D). After 48 h of incubation, cultures were harvested and supernatant was used for LCMS analysis.

Extraction of metabolites and HPLC analysis
Cultures were harvested (10,0006g, 4uC, 10 min) and supernatant was concentrated to dryness under vacuum in rotary flash evaporator (Heidolph, Germany) at 45uC. After complete dryness, the brown residue obtained was fractionated according to the protocol used by Powell [22]. Indolic fractions were evaporated to dryness using flash evaporator, redissolved in HPLC grade methanol (1 ml), filtered (0.22 mm membrane, SUPRO Millipore) and used for HPLC and mass spectrometric analysis. HPLC analysis was performed according to Mujahid et al [19]. HPLC was performed on Prominence LC20AT system (Shimadzu-Japan) equipped with diode array detector and Phenomenex C-18 column (Luna 5 mm, 25064.6 mm). Metabolites were separated by using a linear gradient programme of 30 min (Solvent A; 1% acetic acid, solvent B; 100% acetonitrile) with a flow rate of 1.5 ml/min. Injection volume was 20 ml and metabolites were detected at 280, 325 nm. The metabolites, aniline (R t ; 5.4 min), tryptophan (9.5 min), anthranilate (14.5 min), indole-3-aldehyde (18.5 min) and indole-3-acetic acid (19.1 min) were quantified with reference to the peak areas of known concentrations of authentic standards. Fumarate was measured directly from culture supernatants by using the same HPLC method (as described above) except that fumarate was monitored at 230 nm. Culture supernatant was filtered (0.22 mm membrane, SUPRO Millipore), 20 ml of filtrate was injected into HPLC and fumarate (R t 2.45 min) was quantified with reference to peak areas of known concentrations of authentic standard.

ESI-LC-MS/MS analysis
Mass analysis was performed according to Mujahid et al [19] on MicroTOF-Q (Brukarsdeltanoics) mass spectrometer coupled to HPLC (Agilent 1200 series) with UV-VIS detector. Metabolites were separated on Waters C-18 (5 mm, 15064.6 mm) column. HPLC conditions were as same as described previously, except that the flow rate was 0.8 ml/min and the injection volume was 10 ml. Samples were introduced via auto sampler and metabolites were monitored at 280 nm. With a post column split effluent was introduced into electro spray ionization (ESI) ion source (80uC, Cone voltage 15-25V). ESI (+) and ESI (2) ion modes were used to detect molecular ion masses ([M] + ) and collision energy of 5-20 eV was used for fragmentation depending upon the nature of the molecule. Mass spectra were recorded from 50-1000 Da.

Preparation of cell free extracts and enzyme assays
Control or aniline exposed cells of R. benzoatilyticus JA2 were used for preparation of cell free extracts. Cells were harvested by centrifugation (4uC, 10,0006g, 10 min), the cell pellet was washed twice with Tris-HCl buffer (50 mM, pH 7.8) and suspended in 4 ml of same buffer containing 50 mM PMSF (phenylmethylsulfonyl fluoride). Cells were lysed by sonication with MS-70 probe (Bandelin, German, model-UW 2070) at 45% power, 4uC, 7 cycles of 1 min duration and 5 min gap between each cycle. After sonication, lysate was centrifuged (20,0006g, 20 min, 4uC) and the clear supernatant obtained was used as the source of enzyme. Protein content was measured by Bradford's method [23] using bovine serum albumin as standard.
For the assay of anthranilate synthase activity, the reaction mixture contained 1 mM chorismate, 1 mM glutamine, 50 mM MgCl 2 and cell free extract (1.5 ml) in a final volume of 3 ml. After 30 min of incubation at 37uC, the reaction was stopped by adding 5N HCl (300 ml). Reaction mixture was centrifuged and product (anthranilate) was extracted from the supernatant by ethyl acetate. Ethyl acetate was concentrated and dissolved in methanol and analysed by HPLC as described above. One unit (U) of enzyme activity was defined as the amount of enzyme required for the formation of 1 mmole of product. Specific activity was expressed as unit activity per mg protein.
Assay of tryptophan aminotransferase enzyme activity was carried out in a final volume of 3 ml containing L-tryptophan (1 mM), a-ketoglutarate (1 mM), 50 mM of PLP (pyridoxal-59phosphate) as cofactor and cell free extract (ml) [24]. After 20 min incubation at 37uC, the reaction was stopped by adding 300 ml of 5N HCl. Reaction mixture was centrifuged (4uC for 10 min at 10,000 g) and the supernatant was collected and extracted twice with ethyl acetate. The ethyl acetate layers were pooled, evaporated to dryness under vacuum, dissolved in 100 ml methanol and the product IAA (indolepyruvate is unstable and readily converts into IAA) was analysed by HPLC. Assay of tryptophan 2-monooxygenase enzyme activity was carried [24] out in a final volume of 0.7 ml Tris buffer (50 mM, pH 7.8) containing 0.5 mM of L-tryptophan and appropriate amount of cell free extract (300 ml). Reactions were incubated at 37uC for 20 min and then reaction was stopped by adding 100 ml of 5N HCl. Reaction mixture was centrifuged (4uC for 10 min at 10,0006g) and the supernatant was collected and extracted twice with ethyl acetate. The ethyl acetate layers were pooled, evaporated to dryness under vacuum, dissolved in 50 ml of methanol and the product (indole-3-acetamide) was analysed by HPLC. One unit (U) of enzyme activity was defined as the amount of enzyme required for the formation of 1 mmole (tryptophan aminotransferase) or 1 nmole (tryptophan monooxygenase) of product. Specific activity was expressed as unit activity per mg protein. Pre-denatured enzyme (denatured by adding 300 ml of 5N HCl) was taken as blank.

RNA preparation and quantitative real time RT-PCR
For RNA isolation all the plastic ware was treated with 0.1% (v/ v) DEPC (Diethylpyrocarbonate) overnight, dried and autoclaved. R. benzoatilyticus JA2 was grown photoheterotrophically (0.45 OD 660 nm ) and exposed to aniline as described. 2.5 ml culture was harvested at 60 and 140 min after the aniline exposure, flash frozen in liquid nitrogen and stored at 280uC. RNA was isolated by RNase mini kit (Qiagen) according to manufacturer's instructions. Before RNA isolation, cells were treated with lysozyme (30 mg/ml in Tris.HCl buffer pH 7.0) for 5 min. on column. DNase treatment was performed with DNase I (Qiagen) according to manufacturer's instructions. Isolated RNA was stored at 280uC until further analysis. RNA integrity was analysed on Bioanalyser 2100 and quantity by Nanodrop (Thermo Scientific). DNase treated RNA (925 ng) was reverse transcribed to make 37 ng/ml of cDNA using the Affinity Script QPCR cDNA synthesis kit (Agilent -Lot# 6077352) according to manufacturer's protocol. Real time PCR was performed by using Brilliant II SYBR Green qPCR Master mix (Lot # 1105284). Primers used in real time PCR analysis are listed in Table S1. Each sample was run in duplicates for each gene using 37 ng input per reaction and PCR conditions are as follows; initial denaturation at 95uC for 10 min followed by 40 cycles of 95uC for 30 s, 58uC for 1 min, 72uC for 1 min. A melt curve was also performed after the assay to check for specificity of the reaction. Real time PCR was performed on Stratagene Mx3005P (Agilent technologies) platform. The relative expression levels of the genes were determined after normalizing with 16S rRNA (reference gene) by using Delta Ct method [25].

Time course of aniline and fumarate utilization and indoles production
Utilization of aniline and fumarate was observed with concomitant production of indoles ( Figure 1A). After 48 h of aniline exposure 0.35-0.39 mM indoles were produced while 0.4-0.45 mM of aniline was utilized. Thus yields of indoles were nearly equal to that of aniline utilized.
Tryptophan, IAA, and IAld produced by aniline supplemented culture Tryptophan, indole 3-acetic acid (IAA), and indole 3-aldehyde (IAld) were identified as major indole metabolites in aniline supplemented cultures of R. benzoatilyticus JA2. When tryptophan, IAA, and IAld levels were monitored, tryptophan accumulation (759625 mg/250 ml) was observed only in aniline supplemented cultures while no detectable amount of L-tryptophan was observed in control ( Figure S1A). IAA and IAld were detected both in control and aniline supplemented cultures, however, IAA and IAld levels were significantly high (IAA 175630 mg/250 ml; IAld 96625 mg/250 ml) in aniline supplemented culture compared to that of control (IAA 1063 mg/250 ml; IAld 862.5 mg/250 ml) ( Figure S1A). Time course analysis of tryptophan, IAA, and IAld was performed and no detectable amount of tryptophan was found at zero minutes; tryptophan levels steadily increased from 3 h and reached maximum (1048.5672 mg/250 ml) at 48 h ( Figure 1B) of aniline supplementation. Similarly, IAA and IAld levels increased from 3 h and reached a maximum (IAA 8965 mg/250 ml; IAld 6263 mg/250 ml) at 72 h ( Figure 1B). Tryptophan levels were significantly high (1048.5672 mg/250 ml) compared to that of IAA (8965 mg/250 ml) and IAld (IAld 6263 mg/250 ml) and rate of tryptophan accumulation was also high ( Figure 1B). Tryptophan production increased with increasing concentration of aniline and tryptophan/indoles production was high at 25 mM of aniline ( Figure S1B).
Probing indoles biosynthesis by aniline-d 5 stable isotope feeding reveals that aniline is not a precursor of indoles To evaluate the role of aniline, cells were cultured with deuterium labeled and unlabeled aniline; indoles were extracted from supernatant and analyzed by mass spectrometry. If aniline acts as a precursor of indoles, molecular mass of indole would increase by 4 mass units (+4 a.m.u.as aromatic ring retains four deuterium atoms; Figure S2A). Increase of four mass units was not observed in mass spectrum of tryptophan from labeled aniline fed culture (molecular ion mass of tryptophan, 205.10 [M+H]; Figure  S2B) Figure  S3). This result indicated that aniline was not a precursor of indoles (tryptophan, IAA, IAld).
Indoles are synthesized via the shikimate pathway in aniline exposed cells Aromatic metabolites (including tryptophan/indoles) are biosynthesized via the shikimate pathway in bacteria and plants [26]. The role of the shikimate pathway in indoles production can be ascertained by using glyphosate, an inhibitor of the enzyme enoylpyruvyl shikimate phosphate synthase from the shikimate pathway [26]. When glyphosate (1 mM) was added to the media, growth of R. benzoatilyticus JA2 was inhibited as the cells were starved of aromatic amino acids. When the culture was then supplemented with aromatic amino acids (150 mM) growth was completely restored (data not shown) indicating that shikimate pathway was operative in R. benzoatilyticus for aromatic aminoacid synthesis since glyphosate specifically inhibits the shikimate pathway blocking aromatic amino acid synthesis/production. Aniline is a structural analogue of anthranilate (tryptophan precursor). We tested whether aniline could act as precursor for tryptophan biosynthesis. Growth inhibition of R. benzoatilyticus JA2 (Figure 2A, for 22 hrs) could be resumed and was completely restored when the culture was supplemented with phenylalanine, tyrosine, and anthranilate. However, when anthranilate was replaced with aniline, growth did not resume (Figure 2A), confirming that aniline is not a precursor of tryptophan synthesis. Furthermore, glyphosate inhibited the production of indoles by aniline supplemented cultures in a dose dependent manner ( Figure 2B). Strain JA2 produces indoles when supplemented with anthranilate, and when glyphosate was added to the anthranilate supplemented culture, production of indoles was not inhibited, whereas in aniline supplemented cultures production was inhibited ( Figure 2C). These results indicate that aniline is not a precursor of indoles, rather indoles are de novo synthesized by the shikimate pathway in the presence of aniline. Tryptophan, IAA, and IAld production was significantly inhibited when glyphosate was added to the culture compared to that of no glyphosate ( Figure 2D). These results unequivocally demonstrate that indoles were biosynthesized via the shikimate pathway in aniline supplemented cultures.
Indoles production by aniline exposed cells is dependent on carbon source availability Supplementation of carbon sources to aniline exposed cells of Rhodobacter sphaeroides OU5 enhanced the production of indoles [27]. Similarly, production of indoles was high (0.3460.06 mM (fumarate), 0.2860.04 mM (pyruvate), 0.2560.05 mM (malate) when carbon sources were supplemented to the culture compared to without supplementation (0.01260.04 mM). Further, when both pyruvate and fumarate were supplemented to aniline exposed cells, indoles production significantly increased (0.4160.06 mM). Moreover, when a non-metabolisable carbon source such as maleate was supplemented to aniline exposed cells, indole production was significantly decreased (0.07 mM) and these results indicate that metabolizable carbon sources enhance indole production.
When strain JA2 was exposed to aniline with and without supplementation of fumarate (to understand the role of fumarate in indoles production), tryptophan (462 mg.250 ml 21 ), IAA (117 mg.250 ml 21 ), and IAld (72 mg.250 ml 21 ) levels were high in fumarate supplemented cultures while in absence of fumarate, tryptophan (236 mg.250 ml 21 ), IAA (42.5 mg.250 ml 21 ), and IAld (15 mg.250 ml 21 ) levels were low ( Figure 3A). Further, when similar experiments were performed with resting cell suspensions, tryptophan, IAA, and IAld production was significantly high in fumarate supplemented cultures compared to cultures without fumarate supplementation ( Figure 3B). These results suggest that fumarate is a possible precursor of indole metabolites.

Fumarate is the precursor of indole metabolites
To confirm whether fumarate is a precursor of indoles or not, deuterium labeled (fumarate-d 4 ) or unlabeled fumarate was supplemented to strain JA2 during aniline exposure, and indole metabolites were extracted and subjected to mass analysis.  Figure S4B) and an increase of molecular ion mass (1 to 4 units) of these fragments from labeled fractions ( Table. S2) suggest that deuterium atoms to be on indole molecule. These results strongly confirm that fumarate is precursor of indoles (tryptophan, IAA, and IAld) synthesis in R. benzoatilyticus JA2.

Induction of anthranilate synthase activity correlates with indoles production in aniline supplemented cultures
Anthranilate synthase participates in the first committed step of tryptophan biosynthesis and it is a rate limiting step [26]. Anthranilate synthase activity was monitored and specific activity of anthranilate synthase was significantly high (78.5 U mg protein 21 ) in aniline exposed cultures compared to that of unexposed culture (24.7 U mg protein 21 ). Correlation between induction of anthranilate synthase activity and tryptophan/indoles accumulation indicate its role in indoles synthesis.
Real time PCR (qRT-PCR) analysis of shikimate pathway genes reveals up-regulation of anthranilate synthase gene but not other genes Real time PCR analysis of 3-deoxy-D-arabinoheptulosonate 7phosphate (DAHP) synthase (AroG), chorismate synthase (AroC), chorismatemutase (AroQ), anthranilate synthase (TrpE), tryptophan synthase-b subunit (TrpB) genes was performed to check the transcript levels of these genes in aniline exposed and unexposed cultures. Significant changes in the transcript levels of selected genes was not observed at 20 min of aniline exposure. Chorismate mutase (AroQ) (5.5 fold) and anthranilate synthase (TrpE) (5.6 fold) genes were up-regulated in aniline exposed cells compared to control after 60 minutes of aniline exposure ( Figure 6A). Significant change was not observed in expression of DAHP synthase (AroG1and G2), chorismate synthase (AroC) or tryptophan synthaseb genes (TrpB).
Induction of tryptophan aminotransferase (TAT) and tryptophan 2-monooxygenase (TMO) activities correlates with IAA accumulation IAA and IAld were two major indole metabolites identified in aniline exposed cultures and IAA synthesis from tryptophan was reported in strain JA2 previously [24]. Tryptophan aminotransferase (TAT) and tryptophan 2-monooxygenase (TMO) participate in first step of tryptophan catabolism leading to the formation of IAA. Assay of enzyme activities of TAT and TMO were performed and specific activities of tryptophan aminotransferase (12.2 U mg protein 21 ) and monooxygenase (7.8 U mg protein 21 ) were significantly high in aniline exposed cultures compared to that of unexposed (aminotransferase, 4.9 U; monooxygenase, 2.8 U mg protein 21 ) ( Figure 6B).

Discussion
Bacteria are constantly exposed to biotic and abiotic cues, and one such cue is aromatic compounds. One such aromatic compound, aniline, is degraded by different groups of bacteria. Transformation of aniline to anthranilate was reported in Rhodococcus and possible transformation of aniline to indole is reported elsewhere in bacteria [17]. Indole metabolites were observed in aniline exposed cultures of few purple bacteria [19]. Accumulation of indole derivatives in aniline supplemented cultures and reports of aniline transformation to anthranilate, a precursor of indole/tryptophan, suggested that aniline may be a precursor of indoles. Surprisingly, in the present study with stable isotope labeled aniline feeding, inhibition of indoles production by glyphosate ( Figure 2B) indicated that aniline is not a precursor of tryptophan/indoles. Though aniline is not used as carbon source or as precursor of indoles by strain JA2, uptake of aniline (0.45 mM) was observed and this suggests a possible transformation of aniline to some metabolites which are yet be identified. However, aniline is required to induce indoles production by an unknown mechanism and this may be a stress response to aniline. Stress induced indoles accumulation is reported in bacteria. For example, stresses like antimicrobial [28][29][30], xenobiotic [17,31], nutritional (carbon, nitrogen starvation)/environmental (pH, temperature, growth phase of culture) [32] and oxidative stress [28][29][30] stimulated indoles synthesis. Ethanol (stress) induced tryptophan accumulation is reported in yeast [33] and in plants wide a variety of abiotic [34,35] or biotic cues trigger accumulation of tryptophan and its derivatives [36][37][38]. Acifluorfen (herbicide) triggered synthesis of an indolic compound (camalexin) in Arabidopsis thaliana [39] and methanol triggered accumulation of tryptophan/its derivatives in rice [34]. Diverse group of bacteria produce indole metabolites and production of indoles is reported to have fitness benefit to bacteria under different physiological conditions [40][41][42]. However, role of de novo pathway of indoles and its regulation under stress is not understood well in bacteria.
Indoles accumulation in this study was dependent on carbon source availability ( Figure 3A, B) and this plausibly suggests de novo synthesis. Many aromatic compounds including indoles are de novo synthesised via the shikimate pathway in bacteria and plants [43]. In this study, when de novo synthesis was blocked by glyphosate (shikimate pathway inhibitor), indoles production was inhibited ( Figure 2B); moreover, inhibition was observed only in aniline exposed cells but not in anthranilate ( Figure 2C) or tryptophan (data not shown) supplemented cultures. This is presumably because glyphosate inhibits 5-enolpyruvylshikimate 3-phosphate synthase, the penultimate enzyme of chorismate synthesis [44], which is required for tryptophan/indoles biosynthesis, thus strongly suggesting that indoles are biosynthesised via the shikimate pathway in aniline exposed cells. Similarly, glyphosate inhibited the stress (oxidative) induced accumulation of tryptophan and its derivative (camalexin) in Arabidopsis [39] and tryptamine accumulation in rice infected with Magnaporthegrisea, which were known to synthesise indoles via shikimate pathway [45]. However, de novo synthesis requires a plausible flux of carbon and energy towards tryptophan/indoles synthesis. In support of this we found enhanced production of tryptophan, IAA and IAld in fumarate supplemented conditions ( Figure 3A,B) and this suggests the possible role of fumarate as a carbon and energy source. Furthermore, fumarate stable isotope precursor feeding studies (Figure 4 and 5) confirmed fumarate as a precursor of indoles; this result strongly suggests a flux of carbon (fumarate) to tryptophan biosynthesis. Aromatic compounds synthesis is a complex metabolic process and availability of precursors, erythrose-4-phosphate (E4P) and phosphoenolpyruvate (PEP) are critical for their production [46]. Proteome analysis of aniline exposed cells revealed up-regulation (unpublished data) of two key enzymes, transketolase (tkt) and phosphoenolpyruvate carboxykinase (pck), involved in synthesis of E4P, PEP and this may result in increased pool of precursors for Trp synthesis. Over expression of tkt and pck genes in bacteria enhanced the aromatic compounds/tryptophan production by providing precursors (E4P, PEP) [43,47]. Upregulation of tkt and pck genes possibly suggests a flux of fumarate to the pentose phosphate pathway and gluconeogenesis. Carbon flow from the shikimate pathway towards tryptophan biosynthesis is regulated by anthranilate synthase (TrpE), a key enzyme of tryptophan biosynthesis, and is subject to transcriptional and feedback regulation by tryptophan [48]. In this study, increased anthranilate synthase activity and up-regulation of the anthranilate synthase gene ( Figure 6A) corroborated well with the accumulation of tryptophan/indoles in aniline exposed cells. Over expression of the TrpE gene resulted in enhanced production of tryptophan/indoles in bacteria [49]. Up-regulation of anthranilate synthase gene and tryptophan accumulation were observed during biofilm formation of Salmonella entericasvtyphimurium [33] and E. coli. Similarly in Saccharomyces cerevisiae ethanol stress stimulated tryptophan accumulation [41]. Though transcript levels of DAHP synthase, chorismate synthase, and tryptophan synthase genes were not changed significantly in R. benzoatilyticus JA2 ( Figure 6A), accumulation of tryptophan was observed and this suggests that basal level expression of these genes may be sufficient for tryptophan synthesis. In the present study accumulation of IAA and IAld along with tryptophan suggests tryptophan catabolism in aniline exposed cells. This was further supported by increased tryptophan aminotransferase and tryptophan 2-monooxygenase activities ( Figure 6B) involved in Trp catabolism. Tryptophan dependent IAA biosynthesis is predominant in bacteria [42] and two tryptophan dependent IAA biosynthetic pathways were reported in strain JA2 [24]. On the other hand IAld synthesis is not well understood and oxidation (non-enzymatic/non-specific oxidases) of IAA and indole-3-pyruvate is thought to be involved in IAld synthesis [50]. Nevertheless, tryptophan dependent biosynthesis of IAld was reported by our group in strain JA2 [24].
Interestingly, aniline stress induces accumulation of tryptophan and its derivatives in spite of complex biosynthetic and regulatory mechanisms of Trp synthesis in bacteria [48,51]. However, organization of Trp genes and their regulation vary greatly in bacteria and this is governed largely by life style/selective pressure under which the bacteria thrive [51,52]. Beyond being a precursor for proteins, tryptophan also serves other functions such as a precursor for pigments, antibiotics, and secondary metabolites at different physiological/developmental stages and this demands different regulatory mechanisms other than sensing tryptophan for protein synthesis [51,52]. Due to the fact that tryptophan accumulated only in aniline exposed cells (but not in control), we speculate a possible decoupling of tryptophan synthesis (from sensing for protein synthesis) or a different kind of regulatory mechanism enabling cells to overproduce indoles on physiological demand. Biosynthesis of aromatic metabolites and its regulation has not previously been studied in R. benzoatilyticus JA2, and gaining insights into these mechanisms is of particular interest because it overproduces indoles. Our study demonstrates the role of de novo pathways in indoles production and also demonstrates a metabolic re-programming and shift towards tryptophan/indoles biosynthesis in response to xenobiotic (aniline) stress.  . Transcript levels of shikimate, tryptophan biosynthetic genes and tryptophan catabolising enzyme activities. Real time quantitative PCR analysis of shikimate and tryptophan biosynthetic genes in R. benzoatilyticus JA2 (A). Data represents mean standard deviation of two independent experiments with two biological replicates. AroG1/AroG2 corresponds todeoxy-D-arabinoheptulosonate 7-phosphate synthase; AroC, chorismate synthase; AroQ, chorismatemutase; TrpE, anthranilate synthase; TrpB, tryptophan synthase b. Tryptophan catabolizing enzyme activities of control and aniline exposed cultures of R. benzoatilyticus JA2 (B). Tat, tryptophan aminotransferase; Tmo, tryptophan 2-monooxygenase. Data represents mean standard deviation of three independent experiments. *, p,0.05 compared with control exposed cells obtained from Student's t test. doi:10.1371/journal.pone.0087503.g006 Figure S1 Tryptophan, IAA and IAld levels in control and aniline exposed cultures of R. benzoatilyticus JA2 (A). Tryptophan levels at different concentrations of aniline (B). Metabolites were quantified by HPLC and data represents mean standard deviation of three independent experiments. (TIF) Figure S2 Schematic representation of stable isotope labelled aniline precursor feeding experiments with R. benzoatilyticus JA2 (A). M, denotes molecular ion mass and 0, 4 number of deuterium atoms incorporation. Mass spectrum of tryptophan from unlabeled fraction (B) and mass spectrum from labeled fraction (C). (TIF)


extfieldsofstudy: Biology Medicine

text:
Discrimination of the Expression of Paralogous microRNA Precursors That Share the Same Major Mature Form

Background MicroRNAs (miRNAs) are a class of small non-coding RNAs generated from endogenous transcripts that form hairpin structures. The hairpin precursor is processed into two mature miRNAs that form major/minor duplexes. Mature miRNAs regulate gene expression by cleaving mRNA or repressing protein translation. Numerous miRNAs have been discovered via deep sequencing. Many miRNAs are produced from multiple genome sites. These miRNAs are grouped into paralogous families of miRNAs that generate the same major mature form within organisms. Currently, no method of distinguishing the expression of these miRNAs is available. Results In the present study, strategies were developed to discriminate and quantify the expression of paralogous miRNA precursors. First, paralogous miRNA precursors that were differentially expressed in tissues were identified through analysis of the coexpression scores of their major and minor forms based on deep sequencing data. Then the precursors were identified by monitoring the expression of their host gene or minor form using real-time PCR. Finally, precursors were identified by assessing the expression of clusters of miRNA members. These approaches were used to distinguish miR-128-1 and miR-128-2 as well as miR-194-1 and miR-194-2. The mechanism of transcription related to the differential expression of miR-194-1 and miR-194-2 was also investigated. Conclusion This is the first report to distinguish paralogous miRNA copies by analyzing the expression of major-minor pairs, the host gene, and miRNA clusters. Discriminating paralogous precursors can provide useful information for investigating the mechanisms that regulate miRNA gene expression under different physiological and pathological conditions.

Introduction
MicroRNAs (miRNAs) are a class of conserved small molecular non-coding RNAs of about 22 nucleotides in length. They regulate gene expression through mRNA cleavage and translational repression by binding to the 39 untranslated region of the target mRNA. miRNAs also play important roles in cell development, differentiation, proliferation, and oncogenesis. [1][2][3][4] miRNA genes are transcribed to generate pri-miRNAs, which are intergenic and intronic primary RNA transcripts. Pri-miRNAs are processed into <70 nt hairpin precursors (pre-miRNAs) by Drosh. [5,6] The miRNA precursors are then exported into the cytoplasm and recognized by Dicer. They are eventually processed into mature small miRNAs. [6,7] Many miRNAs have been discovered through deep sequencing. [8] Many miRNAs are produced from multiple sites in genome. Closely related miRNAs are grouped into paralogous families that have related functions. [9] Furthermore, some paralogous miRNA genes produce identical nucleotide sequences of major mature forms within organisms. If the miRNA reads map to more than one precursor sequence, it can be difficult to distribute the sequence counts to the correct one. After being processed by Dicer, the miRNA precursor is divided into two different mature miRNAs, a stable major form and an unstable minor form. [10] These two mature miRNAs form a major/minor duplex. Although the minor form degrades rapidly, significant amounts can be detected through deep sequencing. The major form is usually well conserved but the minor form is not. The sequence of the minor form may differ across paralogous precursors. In this way, these paralogous miRNA precursors can be distinguished by detecting the coexpression of major/minor pairs. Some miRNAs are located in the same transcription unit as other RNAs that encode proteins or non-coding RNAs. The miRNA host gene encodes this kind of transcript, which is usually expressed in parallel with host genes. The expression patterns of miRNA host genes are monitored to demonstrate physiologic and pathologic regulation of miRNA expression. [11] More than 40% of miRNAs are located in the introns or exons of other RNA transcripts in a sense or antisense direction. [11] miRNA is usually regulated along with the host gene if they are both in the sense orientation. [12] Paralogous miRNA precursors that share the same mature form may be produced from different host transcripts. In this way, the expression of paralogous precursors may be determined by monitoring the host gene.
A set of two or more miRNAs forms a cluster, which is transcribed in the sense orientation from physically adjacent miRNA genes. miRNA clusters perform important functions by regulating various cellular processes. For example, the most frequently studied miR-17-92 cluster is involved in the development of the heart, lungs, and immune system and in the formation of tumors. [13][14][15] Clustered miRNAs are usually derived from a common primary transcript and coexpressed. [16] Paralogous miRNA precursors that share the same mature form may also be members of different miRNA clusters. In this way, the expression of paralogous precursors may be distinguished by assessing the expression of cluster miRNAs.
Some paralogous miRNA genes were processed to the same major mature form. In this way, it is impossible to distinguish these paralogous miRNA precursors by analyzing the expression of their major forms. In the present study, approaches to the discrimination of the expression of these miRNA precursors were developed based on miRNA deep sequencing data and real time PCR analysis. In addition, the transcription mechanisms related to the differential expression of miRNA precursor family were investigated.

Tissue-specific and -selective expression of paralogous miRNAs
The miRBase database release 19 contains 855 precursor and 1281 mature mouse miRNAs. Of these, 55 paralogous miRNA families were found. These consist of 138 precursors. Tissuespecific expression of these 55 mature miRNAs, which were processed from 138 precursors, was analyzed. PaGeFinder analysis was performed on 55 mature miRNAs based on the reads generated by RNA deep sequencing. The results, shown in Table 1, showed that 19 of these 55 mature miRNAs were expressed in a tissue-specific or -selective manner.
Associations between major and minor mature forms and among clustered miRNAs We now determined whether major and minor mature forms from the same precursor were co-expressed in 15 mouse tissues. Here miRNA precursors with total reads of major form more than 50 in 15 mouse tissues were selected. The Pearson correlation Rvalues and P-values in 419 major/minor pairs were calculated. As shown in Table S5, 304 significantly correlated pairs were found (p,0.01). The expression of 73 percent (304 to 419) of major and minor pairs was positively correlated. We also investigated whether clustered microRNAs are co-expressed. 52 miRNA clusters with inter-miRNA distance,5000 bp (base pair) were selected. Pearson correlation R-values and P-values in 865 miRNA pairs in these clusters were computed. As shown in Table S6, 693 clustered miRNA pairs are significantly correlated (p,0.01) in our datasets. The expression of 80 percent (693 to 865) of clustered miRNA pairs was positively correlated.
Expression profile of paralogous miRNA precursor and major mature form A relative expression analysis of precursors and their corresponding major forms was performed across different mouse tissues. All reads that mapped to particular precursor were used to analyze the expression of that precursor. Reads with the same start position as a particular mature miRNA were also used to analyze the expression of mature miRNA, and the greatest number of reads that mapped to a particular precursor was considered the expression of that major form (Table S2). Each miRNA count from each mouse tissue was normalized to the total number of reads for that tissue. The normalized reads were used to build a heat map using GenePattern software. The results shown in Figure 1 showed the hairpin precursor and the major product to almost always be extremely well matched in the expression profiles of most miRNAs. However, the expression of some precursors including miR-219-1 and miR-219-2, miR-30c-1and miR-30c-2, miR-365-1 and miR-365-2 could be distinguished from the heatmap. miR-219-2 was preferentially expressed in brain, but miR-219-1 was preferentially expressed in spleen and lymph nodes. miR-365-2 was preferentially expressed in kidney, but miR-365-1 was not.

Discrimination of paralogous precursors using the coexpression of major and minor forms
To distinguish the expression of paralogous precursors that share the same major mature form, we determined the occurrence of major/minor pairs in 15 normal mouse tissues. The biological hypothesis tested here involved analysis of the coexpression of two forms of miRNAs in the same tissue. Coexpression was considered indicative of precursors with high probability of being processed into the corresponding major/minor pair. The miRNA precursors were first excluded if the expression of major and minor forms in this precursor family were not significantly associated by Pearson's Table 1. Identification of miRNAs tissue specifically or selectively expressed.
Host gene expression of miRNA as a proxy for distinguishing paralogous precursor The host gene of miR-128-1 and miR-128-2 here served as an example in a demonstration of the current method of distinguishing the expression of paralogous miRNA precursors. Both mmumir-128-1 and mmu-miR-128-2 are intronic miRNAs. mmu-mir- Figure 1. Expression of miRNA precursor and its major mature form in 15 mouse tissues. A heat map was constructed using GenePattern software based on the normalized miRNA reads. Heat maps showed precursors and major forms to have similar patterns of expression. doi:10.1371/journal.pone.0090591.g001   128-1 resides in the 16 th intron of the R3HDM1 gene on mouse chromosome 1qE3 ( Figure 3A). mmu-miR-128-2 is embedded in the 17th intron of the ARPP21 gene on mouse chromosome 9qF3 ( Figure 3B). mmu-miR-128-1 is processed into miR-128-3p and miR-128-1-5p. mmu-miR-128-2 is processed into miR-128-3p and miR-128-2-5p. miR-128-3p is the common major mature form of miR-128-1 and 2. The results shown in Table 1 show that miR-128-3p was selectively expressed in the brain and thymus. As shown in Table S3 and Table 2, the coexpression scores of miR-128-3p and miR-128-2-5p were 64394 and 8628 in the thymus and brain, respectively. The coexpression scores of miR-128-3p and miR-128-1-5p were 0 and 7241 in the thymus and brain, respectively. We further investigated the expression of R3HDM1 and ARPP21 gene in 16 mouse tissues using real time PCR. The results shown in Figure 3C and Figure 3D indicate that ARPP21 was selectively expressed in the thymus and brain, but R3HDM1 was not. The expression of minor mature forms miR-128-1-5p and miR-128-2-5p in 16 mouse tissues was assessed using real time PCR. We found miR-128-2-5p was selectively expressed in the thymus and brain ( Figure 3E and Figure 3F). Next we determined whether miR-128-3p and its host genes, R3HDM1 and ARPP21, are co-expressed. Expression value of R3HDM1 and ARPP21 mRNA (Real-time PCR) and read counts of miR-128-3p (deep sequencing) in mouse tissues were obtained. Pearson correlation R-values and P-values of R3HDM1/miR-128-3p pair and ARPP21/miR-128-3p pair were computed. We found that the expression of ARPP21 and miR-128-3p was significantly correlated (R = 0.98, P,0.05) but the expression of R3HDM1 and miR-128-3p was not (R = 0.48, P = 0.134). These results suggest that miR-128-2 is the major contributor to the expression of miR-128-3p in the thymus, but miR-128-1 is not.

Identification of paralogous miRNA precursors by the coexpression of cluster miRNAs
Here, the cluster containing miR-194-1/miR-215 and miR-194-2/miR-192 served as an example of how to distinguish the expression of paralogous miRNA genes. The mmu-miR-194-1 precursor is processed into miR-194-5p and miR-194-1-3p. mmu-miR-194-2 is processed into miR-194-5p and miR-194-2-3p. miR-194-5p is the common major mature form of miR-194-1 and miR-194-2. The results shown in Table 1 above indicate that miR-194-5p was selectively expressed in the liver and kidneys. As shown in Table 2, the coexpression scores of miR-194-5p and miR-194-1-3p were 0 and 0 in the liver and kidneys, respectively. The coexpression scores of miR-194-5p and miR-194-2-3p were 783 and 987 in the liver and kidneys, respectively. miR-194-1 was found to cluster with miR-215 and miR-194-2 was found to cluster with miR-192. The coexpression of miR-194-5p and miR-192-5p and of miR-194-5p and miR-215-5p was calculated. As shown in Table 3, the coexpression scores of miR-194-5p and miR-215-5p were 0 in the liver and kidneys, respectively. The coexpression scores of miR-194-5p and miR-192-5p were 77,872 and 96,655 in the liver and kidneys, respectively. The expression of miR-194-5p, miR-192-5p, and miR-215-5p in 16 mouse tissues was assessed using real time PCR. miR-194-5p and miR-192-5p were selectively expressed in the gastrointestinal tract, liver, and kidneys ( Figure 4A, B). However, miR-215 was found to be specifically expressed in the gastrointestinal tract but not in the liver or kidneys ( Figure 4C). miR-215p also has much lower levels of expression in the gastrointestinal tract, liver, and kidney than miR-192-5p. Deep sequencing miRNA data are not available for the mouse gastrointestinal tract. However, such data are available for human cell lines DLD2 and SW480, isolated from the colon. The expression of miR-194-5p, miR-192-5p, and miR-215-5p were determined in DLD2 and SW480 cells. The results shown in Table 4 and Figure 5 indicate that both miR-194-5p and miR-192-5p are much more highly expressed in DLD2 and SW480 cells than miR-215-5p is. These results suggest that mmu-miR-194-2 was selectively expressed in the gastrointestinal tract, liver, and kidney and that mmu-miR-194-1 was specifically and minimally expressed in the gastrointestinal tract. Mmu-miR-194-2 is the major contributor to the expression of miR-194-5p in the gastrointestinal tract, liver, and kidneys.

Mechanism of tissue differential expression of paralogous miRNA precursors
Results showed miR-194-2 to be a major contributor to the expression of miR-194-5p in the liver and kidneys and showed the contribution of miR-194-1 to be negligible or nonexistent. Here the mechanism of differential expression of miR-194-1 and miR-194-2 was investigated. Based on the previously reported gene structure of pri-miR-194-2/miR-192, 2 kb promoter sequences of human, mouse, rat, and bovine pri-miR-194-2/miR-192 genes were downloaded. [17] In addition, by searching NCBI and UCSC genome database, cDNA AK008306 was found to be part of the transcript of pri-miR-194-1/miR-215. Based on the transcription start site of cDNA AK008306, 2 kb promoter sequences of mouse pri-miR-194-1/miR-215 gene were downloaded. Homologous analysis was used to identify and download 2 kb putative promoter sequences of rat and human pri-miR-194-1/miR-215 genes. HNF1a was found to induce the expression of miR-194 in the intestine. [17] HNF1a, HNF4a, and HNF4b were found to be expressed preferentially in the liver, intestine, and kidneys. [18,19] The promoter sequence of pri-miR-194-2/miR-192 and pri-miR-194-1/miR-215 was then analyzed using Motif-based sequence analysis tools (http://meme.nbcr.net). A conserved HNF1 binding site and a conserved HNF4 binding site were found in the pri-miR-194-2/miR-192 gene promoter region with expected P values below 0.001 ( Figure 6). However, no conserved HNF1 or HNF4 binding sites were found in the pri-miR-194-1/miR-215 gene promoter. pri-miR-194-2/miR-192 and pri-miR-194-1/miR-215 gene promoters were found to be conserved across HNF4 binding sites, but a two-nucleotide deletion, CC, was observed in the HNF4 binding motif in pri-miR-194-1/miR-215 gene promoters. This may be connected to the loss of expression of pri-miR-194-1/ miR-215 genes in the kidneys and liver.

Discussion
Strategies for distinguishing the tissue expression pattern of paralogous miRNA precursors that share the same major mature form are here discussed. The hairpin miRNA precursor is processed into a major/minor pair. Because the minor form is less conserved and more likely to differ across paralogous precursors, it is possible to distinguish those paralogous precursors by the minor form that they produce. Products of minor miRNA have been successfully used to distinguish miR-2a-1 and miR-2a-2 Figure 2. Expression of the miRNA precursor and its major and minor mature forms in 15 mouse tissues. Heat maps were constructed using GenePattern software based on the normalized miRNA reads. This heat map shows precursors and minor forms to have different patterns of expression in many paralogous families. doi:10.1371/journal.pone.0090591.g002 in Drosophila. [20] Here, the statistical significance of the occurrence of major/minor pairs in specific tissues was computed using online datasets showing mice miRNA deep sequencing information. Based on the coexpression score of the major/minor pair and Fisher exact test, 19 of 42 paralogous families were found to be differentially expressed in tissues ( Table 2 and Table S3). No differential expression was detected among miR-124-1, miR-124-2, and miR-124-3 or among miR-9-1, miR-9-2, and miR-9-3, which are specifically expressed in the brain, using this approach because they produce the same major and minor forms. Real-time PCR was developed to determine the expression of 70 nt hairpin miRNA precursors. [21] Direct analysis of precursor expression through real-time PCR may also be used to discriminate the paralogous family, including precursors that could not be distinguished. However, these paralogous precursors have high degrees of sequence identity. The primers designed in this way may have partially or completely identical sequences. In this way, specificity is an important factor and must be considered. In the present study, deep sequencing data was used to distinguish the expression of paralogous precursors based on differences as slight as a single nucleotide in the minor form.
Several studies have reported strand selection of miRNA expression. [10,22,23] About half of all miRNA duplexes have been found to have a highly dominant strand, as indicated by comparison of miRNA/miRNA* ratios across the miRNA sequence libraries. [24] Due to strand selection bias, the proportion of reads derived from each arm of a given hairpin can differ greatly across different tissues, even to the extent that the major and minor forms can switch. To assess the prevalence of changes in arm usage in the datasets, expression ratios between major and minor miRNAs were determined in 419 pairs with more than 50 reads. A broad range of differences were found. An expression ratio greater than 400 was observed for 135 miRNA pairs, but it was less than 10 for 132 miRNA pairs (see Table S4). miRNAs with the expression ratios around 2 were found to switch major and minor forms in different tissues. Strand selection bias exists for some miRNA pairs in these datasets. Strand selection bias can produce differences in the levels of expression within some miRNA pairs. The details of selection mechanisms have not yet been fully determined. The sequence features of mature forms are likely to be linked to strand selection bias within the human miRNA pairs. [25] Because members of miRNA precursor families are processed to the same major form, strand selection bias may be similar. Major and minor forms are processed from the same precursor, so the expression of major and minor forms may be correlated. We found that the expression of 73 percent of major and minor pairs was positively correlated by Pearson's correlation analysis. It is reasonable to distinguish the expression of multiple hairpins that express the same major mature miRNA by looking at the differences in the co-expression scores of major/minor pairs. Statistical analyses were used in the present study. Only the top 10% of the scored major and minor pairs were selected. The two tailed Fisher's exact test was performed to further justify the selection. Again other strategies (co-expression of host gene and cluster members) were used to validate the identification.
More than half of known mammalian miRNAs are located in the same transcription unit as protein-coding RNAs and other noncoding RNAs. [26] These miRNAs are transcribed in parallel with their host genes. [11] Several studies assess the correlation of expression between intragenic miRNAs and their host genes. 41 intragenic miRNA/host gene pairs were found to be positively correlated using NCI-60 data. [27] In addition, evolutionarily conserved intragenic miRNAs tend to be co-expressed with their host genes in human based on miRNA and mRNA microarray data. [28] miRNA precursors from the same paralogous miRNA family may be located in different host genes. In this way, the expression patterns of paralogous precursors can be distinguished by determining the expression of microRNA host genes. In the current study, the patterns of expression of mmu-miR-128-1 and mmu-miR-128-2 were clarified by assessing the expression of host genes R3HDM1 and ARPP21. miR-128-3p is the common major form of mmu-miR-128-1 and mmu-miR-128-2, and it was found to be selectively expressed in the brain and thymus ( Table 1). The major/minor pair miR-128-3p/miR-128-2-5p was found to have a much higher coexpression score in the thymus than the pair miR-128-3p/miR-128-1-5p, but this was not the case in the brain ( Table 2). The expression of ARPP21 and R3HDM1 was assessed in 16 mouse tissues. Results showed ARPP21 to be selectively expressed in the brain and the thymus, but R3HDM1 was not ( Figure 3C and 3D). The expression of the minor mature forms miR-128-1-5p and miR-128-2-5p were investigated in 16 mouse tissues. Like the host gene ARPP21, miR-128-2-5p was preferentially expressed in the thymus and the brain ( Figure 3E and 3F). Moreover, the expression of miR-128-3p and ARPP21 was significantly correlated by Pearson's correlation analysis. These results suggest that mmu-miR-128-1 and mmu-miR-128-2 are differentially expressed in the thymus. mmu-miR-128-2 is the major contributor to the expression of miR-128-3p in the thymus. Both mmu-miR-128-1 and mmu-miR-128-2 contribute to the expression of miR-128-3p in the brain. miRNA genes are distributed across chromosomes either individually or in clusters. A miRNA cluster is a group of miRNA genes located within a short distance of each other on the same of the expression of miR-128-1-5p and miR-128-2-5p, the levels of expression were normalized to U6 snRNA. * Preferential expressed tissues identified by ANOVA (P,0.05) and Turkey's HSD test. doi:10.1371/journal.pone.0090591.g003 Table 3. Tissue coexpression score of miR-194-5p/miR-215-5p and miR-194-5p/miR-192-5p. chromosome. The miRBase database defines this distance as 10 kb. [29] Almost half of D. melanogaster miRNA genes are grouped in genomic clusters. [30] Although miRNAs from almost all clusters have similar tissue expression profiles, some clusters contain miRNAs with uncoordinated expression profiles. The expression of 80 percent of clustered miRNA pairs were positively correlated in our datasets. The post-transcriptional regulation of miRNA maturation can be considered a possible cause of uncoordinated expression of clustered miRNAs. [30] Paralogous precursors that share the same major form may be derived from different miRNA clusters. The expression of these precursors can be distinguished by determining the expression of cluster miRNAs. miR-194-5p, which is the common major form of miR-194-1 and miR-194-2, was found to be selectively expressed in the kidneys and liver ( Table 1). The miR-194-1/miR-215 and miR-194-2/ miR-192 clusters were processed into the same mature form miR-194-5p. Using major/minor coexpression analysis, mmu-miR-194-2 was found to be preferentially expressed in the liver and kidneys, but not mmu-miR-194-1 ( Table 2). The miR-194-1/ miR-215 and miR-194-2/miR-192 cluster served as an example and is here used in a demonstration of how to distinguish the expression of paralogous miRNA genes by analyzing the expression of cluster members. miR-194-5p and miR-192-5p are co-expressed in the liver and kidneys. Using real-time PCR, it was confirmed that mmu-miR-194-2 is preferentially expressed in the liver, kidneys, and the gastrointestinal tract by analyzing the expression of miR-194-5p, miR-192-5p, and miR-215-5p in 16 mouse tissues ( Figure 4A, 4B, and 4C). Because some clusters were found to contain miRNAs with uncoordinated expression  profiles, it is necessary to use coordinated clusters to distinguish the expression of paralogous miRNA genes. The mechanism underlying the differentially expression of paralogous precursors is as follows. Transcription of the promoter and the processing of pri-miRNAs and precursors can affect miRNA expression. The mechanism by which mmu-miR-194-1 and mmu-miR-194-2 are differentially expressed in tissues was determined. The pri-miR-194-2/miR-192 gene promoter was found to have conserved HNF1 and HNF4 binding sites. Like the pri-miR-194-2/miR-192 gene, HNF1 and HNF4 are transcription factors selectively expressed in the liver, kidneys, and intestines. [18,19] These results suggest that the difference in the transcription binding site of the miRNA gene promoter may be linked to the differential expression of paralogous precursors in tissues.
In summary, multiple strategies for distinguishing paralogous miRNA precursors that share the same major mature form were demonstrated. These strategies may facilitate investigations of the mechanisms underlying the regulation of miRNA gene expression in different tissues.

miRNA sequence reads and heat map of miRNA expression
MiRBase is the primary online miRNA sequence and annotation database. Recently, short RNA deep-sequencing data were incorporated into the miRbase, facilitating detailed miRNA annotation. Each small RNA sequence read is mapped to the stem-loop sequence with detailed information of count number and start position per each experiment. A full report of annotations from miRBase release 19 was downloaded for 15 mouse tissues, including the name of precursor and mature miRNA, cluster information, the numbers and positions of mapped reads, and experimental information (http://www.mirbase.org). The reads that mapped to the same start position for each miRNA precursor without any mismatch under experimental conditions were then recorded. The miRNA guide strand (processed into the major form) and passenger strand (processed into the minor form) arm were defined for each miRNA precursor. The position with the highest number of reads was considered the location of authentic major mature miRNA and of guide strand arm. The highest sum of reads was used to calculate the expression of major form. The alternative arm from the same precursor was here defined as the passenger strand, and the highest number of reads in this strand was used to calculate the expression of the minor form. Each miRNA count from each type of mouse tissue was normalized to the total number of reads for that type of tissue. The normalized reads were used to build a heat map using GenePattern software. [31] To determine the prevalence of changes in arm usage in 15 mouse tissues, expression ratios between major and minor miRNAs in 419 pairs with more than 50 reads were determined. miRNA deep sequencing data for human colon cell lines were downloaded from the GEO database in NCBI under accession numbers GSM416758 and GSM416759. Mapped reads that showed no mismatches for miR-194-5p, miR-192-5p, and miR-215-5p were extracted.

Tissue coexpression of major/minor miRNA pairs
Tissue coexpression scores of major and minor miRNAs were determined using previously described methods. [32,33] Mapped microRNA reads are summarized in one matrix. The matrix showed one column per tissue and one row per miRNA, including precursors, major forms, and minor forms. miRNAs with total reads more than 50 were selected. There were 237 miRNAs in 15 different tissues. These miRNAs were classified into 42 paralogous families.
For an array, define the following: Mij: sequence reads for miRNA i in tissue j Ti: total reads of miRNA i in all 15 tissues Qj: the ratio of the count of all miRNAs in tissue j to the total count of sequence reads of all miRNAs in all 15 tissues.
Zij: the tissue specificity of miRNA i in tissue j Then the tissue coexpression score of major and minor form of miRNA i in tissue j was defined as follows:  Cij(major=minor)~Zij(major) Ã Zij(minor) The top 10% of the scored major and minor pairs were selected, and then a two-tailed Fisher's exact test was performed to assess the differential expression of minor forms that are processed from the same family of precursors. The minor forms with P values below 0.05 were used as statistical justification for the further selection of major and minor pairs to discriminate the expression of miRNA precursor.

Pearson's correlation coefficient and statistical significance
Pearson's correlation coefficient (R) is a measure of the strength of the correlation between the two variables. It is widely used as a measure of gene coexpression. To test the association between paired major and minor miRNAs, among clustered microRNAs, and between intragenic miRNAs and host genes, the R-value and p-values were computed. [34][35][36] PaGeFinder analysis of tissue-specific expression of mature miRNA Pattern Gene Finder (PaGeFinder) is a free online server to analyze the tissue expression pattern of genes. [37] PaGeFinder implements new algorithms and functions for quantitative identification of pattern genes like specific and selective genes, housekeeping genes, and repressed genes. Tissue-specific expression of mature miRNAs was performed using PaGeFinder analysis. The normalized reads of major mature miRNAs were subjected to analysis. The search criteria was set at SPM.0.9 for the identification of miRNAs that underwent tissue-specific expression or at SPM.0.5 and CTM.0.9 for the identification those that underwent tissue-selective expression.
Isolation of RNA from mouse tissues C57BL/6J mice aged 8-12 weeks were purchased from the Soochow University Animal Center. They were housed in a temperature-and humidity-controlled room and supplied with rodent chow and water. Mice were anesthetized intraperitoneally with ketamine and xylazine and then killed. Samples of the thymus, spleen, brain, eye, lung, heart, liver, kidney, adrenal gland, urinary bladder, stomach, intestine, skin, skeletal muscle, testis, and ovary were collected. The animal experiment in this study was approved by the Soochow University Animal Center, Jiangsu Province, China. Total RNA was extracted and isolated by using Tri Reagent from about 30-50 mg mouse tissues according to the manufacturer's instructions. RNA quality and quantity were assessed using agarose gel electrophoresis and A260/A280 ratio and A260/A230 ratio with spectrophotometer. The A260/A280 ratios for all RNA preparations were greater than 1.9, and the A260/A230 ratios for all RNA preparations were greater than 2.0. miRNA quantitative real time PCR Quantitative real-time PCR (qRT-PCR) was used to determine the expression of mature miRNA in different tissues in mice, as previously reported. The primers are listed in Table S1. In brief, total RNA were treated with DNase and purified using phenol/ chloroform extraction and ethanol precipitation. Then 1 mg of the DNase-treated RNA was poly A tailed and purified using phenol/ chloroform extraction and ethanol precipitation. These poly-Atailed RNA were reverse-transcribed into cDNA with polyT adapter as the primer. The real-time PCR thermal conditions for all mature miRNAs were 95uC for 10 min, followed by 40 cycles of 95uC for 15 s and 60uC for 60 s. Data were analyzed using relative real-time PCR quantification based on the comparative CT method. The endogenous reference gene was U6 snRNA. Single-factor ANOVA (P,0.05) followed by Turkey's honestly significant difference (HSD) test was used to examine the tissue types in which a miRNA expressed preferentially. [38]_EN-REF_27 mRNA quantitative real time PCR Quantitative real-time PCR (qRT-PCR) was used to determine the expression of host gene in different tissues in mice. The primers are listed in Table S1. In brief, 1 mg of total RNA was reversetranscribed into cDNA with dT17, random hexamer primer and MMLV reverse transcriptase. The real-time PCR thermal conditions for all the selected genes were 95uC 10 min, followed by 40 cycles of 95uC for 15 s and 60uC for 60 s. The expression of genes relative to 18S RNA was determined using the comparative CT method. Single-factor ANOVA (P,0.05) followed by Turkey's honestly significant difference (HSD) tests was used to determine the type of tissue in which each gene was preferentially expressed.